Ling Shao 

 

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Publications (Selected Publications)

Books

L. Shao, J. Han, P. Kohli and Z. Zhang (Eds.), Computer Vision and Machine Learning with RGB-D Sensors, Springer-Verlag, 2014.

L. Shao, C. Shan, J. Luo and M. Etoh (Eds.), Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications, Advances in Pattern Recognition Book Series, Springer-Verlag, 2010.

J. Zhang, L. Shao, L. Zhang and G. Jones (Eds.), Intelligent Video Event Analysis and Understanding, Studies in Computational Intelligence Book Series, Springer-Verlag, 2011.

Journal Articles

F. Zheng, Y. Tang and L. Shao, “Hetero-manifold Regularisation for Cross-modal Hashing”, Accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), doi: 10.1109/TPAMI.2016.2645565.

M. Yu, L. Liu and L. Shao, “Structure-Preserving Binary Representations for RGB-D Action Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38, no. 8, pp. 1651-1664, Aug. 2016.

M. Yu, L. Shao, X. Zhen and X. He, “Local Feature Discriminant Projection”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38, no. 9, pp. 1908-1914, Sep. 2016.

L. Liu, M. Yu and L. Shao, “Latent Structure Preserving Hashing”, International Journal of Computer Vision (IJCV), vol. 122, no. 3, pp. 439-457, May 2017.

D. Wu, L. Pigou, P.-J. Kindermans, N. Le, L. Shao, J. Dambre and J.-M. Odobez, “Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38, no. 8, pp. 1583-1597, Aug. 2016.

L. Shao, L. Liu and M. Yu, Kernelized Multiview Projection for Robust Action Recognition, International Journal of Computer Vision (IJCV), vol. 118, no. 2, pp. 115-129, Jun. 2016.

M. Yu, L. Liu and L. Shao, “Binary Set Embedding for Cross-modal Retrieval”, Accepted by IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2016.2609463.

L. Liu, M. Yu and L. Shao, “Learning Short Binary Codes for Large-scale Image Retrieval”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1289-1299, Mar. 2017.

J. Xie, F. Zhu, G. Dai, L. Shao and Y. Fang, “Progressive Shape-Distribution-Encoder for Learning 3D Shape Representation”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1231-1242, Mar. 2017.

Y. Guo, G. Ding, L. Liu, J. Han and L. Shao, “Learning to Hash with Optimized Anchor Embedding for Scalable Retrieval”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1344-1354, Mar. 2017. 

Z. Zhang, Z. Lai, Y. Xu, L. Shao and G. S. Xie, “Discriminative Elastic-Net Regularized Linear Regression”, IEEE Transactions on Image Processing, vol. 26, no. 3, pp. 1466-1481, Mar. 2017.

Y. Tang and L. Shao, “Pairwise Operator Learning for Patch Based Single-image Super-resolution”, IEEE Transactions on Image Processing, vol. 26, no. 2, pp. 994-1003, Feb. 2017.

L. Zhang, H. Shum and L. Shao, “Manifold Regularized Experimental Design for Active Learning”, IEEE Transactions on Image Processing, vol. 26, no. 2, pp. 969-981, Feb. 2017.

L. Liu, Z. Lin, L. Shao, F. Shen, G. Ding and J. Han, “Sequential Discrete Hashing for Scalable Cross-Modality Similarity Retrieval”, IEEE Transactions on Image Processing, vol. 26, no. 1, pp. 107-118, Jan. 2017.

X. Dong, J. Shen and L. Shao, “HSP2P: Hierarchical Superpixel-to-Pixel Dense Image Matching”, Accepted by IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2016.2595321, 2016.

B. Ma, L. Huang, J. Shen, L. Shao, M.-H. Yang and F. Porikli, “Visual Tracking under Motion Blur”, IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5867-5876, Dec. 2016.

 

J. Shen, X. Hao, Z. Liang, Y. Liu, W. Wang and L. Shao, “Real-Time Superpixel Segmentation by DBSCAN Clustering Algorithm”, IEEE Transactions on Image Processing, vol. 25, no. 12, pp. 5933-5942, Dec. 2016.

W. Wang, J. Shen, L. Shao and F. Porikli, “Correspondence Driven Saliency Transfer”, IEEE Transactions on Image Processing, vol. 25, no. 11, pp. 5025-5034, Nov. 2016.

B. Ma, H. Hu, J. Shen, Y. Liu and L. Shao, “Generalized Pooling for Robust Object Tracking”, IEEE Transactions on Image Processing, vol. 25, no. 9, pp. 4199-4208, Sep. 2016.

J. Tang, K. Wang and L. Shao, “Supervised Matrix Factorization Hashing for Cross-Modal Retrieval”, IEEE Transactions on Image Processing, vol. 25, no. 7, pp. 3157 – 3166, Jul. 2016. [Code]

F. Zhu, L. Shao, J. Xie and Y. Fang, “From Handcrafted to Learned Representations for Human Action Recognition: A Survey”, Image and Vision Computing, vol. 55, pp. 42-52, Nov. 2016.

D. Ai, J. Yang, J. Fan, Y. Zhao, X. Song, J. Shen, L. Shao and Y. Wang, “Augmented Reality Based Real-time Subcutaneous Vein Imaging System”, Biomedical Optics Express, vol. 7, no. 7, pp. 2565-2585, Jul. 2016.

R. Yan and L. Shao, “Blind Image Blur Estimation via Deep Learning”, IEEE Transactions on Image Processing, vol. 25, no. 4, pp. 1910-1921, Feb. 2016.

L. Zhang, H. Shum and L. Shao, “Discriminative Semantic Subspace Analysis for Relevance Feedback”, IEEE Transactions on Image Processing, vol. 25, no. 3, pp. 1275-1287, Mar. 2016.

F. Zhu, L. Shao and Y. Fang, “Boosted Cross-Domain Dictionary Learning for Visual Categorization”, IEEE Intelligent Systems, vol. 31, no. 3, pp. 6-18, May 2016.

P. Peng, K. Lekadir, A. Gooya, L. Shao, S. E. Petersen and A. F. Frangi, “A Review of Heart Chamber Segmentation for Structural and Functional Analysis Using Cardiac Magnetic Resonance Imaging”, Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 29, no. 2, pp. 155-195, Apr. 2016.

X. Zhen and L. ShaoAction Recognition via Spatio-Temporal Local Features: A Comprehensive Study”, Image and Vision Computing, vol. 50, pp. 1-13, Jun. 2016.

F. Zheng, L. Shao, V. Racic and J. Brownjohn, “Measuring Human-Induced Vibrations of Civil Engineering Structures via Vision-Based Motion Tracking”, Measurement, vol. 83, pp. 44-56, Apr. 2016.

J. Qin, L. Liu, Z. Zhang, Y. Wang and L. Shao, “Compressive Sequential Learning for Action Similarity Labeling”, IEEE Transactions on Image Processing, vol. 25, no. 2, pp. 756-769, Feb. 2016.

X. Dong, J. Shen, L. Shao and L. V. Gool, “Sub-Markov Random Walk for Image Segmentation”, IEEE Transactions on Image Processing, vol. 25, no. 2, pp. 516-527, Feb. 2016.

L. Liu and L. Shao, “Sequential Compact Code Learning for Unsupervised Image Hashing”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 12, pp. 2526-2536, Dec. 2016.

W. Zhang, J. Han, J. Han and L. Shao, Cosaliency Detection Based on Intrasaliency Prior Transfer and Deep Intersaliency Mining”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 6, pp. 1163 – 1176, Jun. 2016.

J. Han, L. Shao, N. Vasconcelos, J. Han and D. Xu, “Guest Editorial Special Section on Visual Saliency Computing and Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 6, pp. 1118 - 1121, Jun. 2016.

L. Nie, L. Zhang, Y. Yan, X. Chang, M. Liu and L. Shao, “Multiview Physician-Specific Attributes Fusion for Health Seeking”, IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2016.2577590.

Y. Xia, L. Zhang, R. Hong, L. Nie, Y. Yan and L. Shao, “Perceptually-Guided Photo Retargeting’, Accepted by IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2016.2520959.

S. Tan, F. Zheng, L. Liu, J. Han and L. Shao, “Dense Invariant Feature Based Support Vector Ranking for Cross-Camera Person Re-identification”, Accepted by IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2016.2555739.

Z. Cai, J. Han, L. Liu and L. Shao, “RGB-D Datasets Using Microsoft Kinect or Similar Sensors: A Survey”, Accepted by Multimedia Tools and Applications, doi: 10.1007/s11042-016-3374-6.

R. A. Manap, L. Shao and A. Frangi, “Non-Parametric Quality Assessment of Natural Images”, IEEE Multimedia, vol. 23, no. 4, pp.22-30, Oct.-Dec. 2016.

L. Liu, M. Yu and L. Shao, “Unsupervised Local Feature Hashing for Image Similarity Search”, IEEE Transactions on Cybernetics, vol. 46, no. 11, pp. 2548-2558, Nov. 2016.

B. Ma, L. Huang, J. Shen and L. Shao, “Discriminative Visual Tracking Using Tensor Pooling”, IEEE Transactions on Cybernetics, vol. 46, no. 11, pp. 2411-2422, Nov. 2016.

K. Wang, J. Tang, N. Wang and L. Shao, “Semantic Boosting Cross-Modal Hashing for Efficient Multimedia Retrieval”, Information Sciences, vol. 330, pp. 199–210, Feb. 2016.

J. Tang, L. Shao, X. Li and K. Lu, “A Local Structural Descriptor for Image Matching via Normalized Graph Laplacian Embedding”, IEEE Transactions on Cybernetics, vol. 46, no. 2, pp. 410-420, Feb. 2016.

L. Liu, L. Shao, X. Li and K. Lu, “Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach, IEEE Transactions on Cybernetics, vol. 45, no. 1, pp. 158-170, Jan. 2016.

B. Ma, Y. Liu, J. Shen, H. Liu, L. Shao and X. Li, “Visual Tracking Using Strong Classifier and Structural Local Sparse Descriptors”, IEEE Transactions on Multimedia, vol. 17, no. 10, pp. 1818-1828, Oct. 2015.

W. Wang, J. Shen and L. Shao, “Consistent Video Saliency Using Local Gradient Flow Optimization and Global Refinement”, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4185-4196, Nov. 2015.

X. Dong, J. Shen, L. Shao and M.-H. Yang, “Interactive Cosegmentation Using Global and Local Energy Optimization”, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3966 – 3977, Nov. 2015.

Q. Zhu, J. Mai and L. Shao, “A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior”, IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 3522–3533, Nov. 2015.

Y. Long, F. Zhu and L. Shao, “Recognising Occluded Multi-View Actions Using Local Nearest Neighbour Embedding”, Computer Vision and Image Understanding, vol. 144, pp. 36-45, Mar. 2016.

Z. Jiang, Z. Lin, H. Ling, F. Porikli, L. Shao and P. Turaga, “Discriminative Feature Learning from Big Data for Visual Recognition”, Pattern Recognition, vol. 48, no. 10, pp. 2961–2963, Oct. 2015.

L. Liu, L. Shao and X. Li, “Evolutionary Compact Embedding for Large-Scale Image Classification”, Information Sciences, vol. 316, pp. 567-581, Sep. 2015.

S. Tan, L. Liu, C. Peng and L. Shao, “Image-to-Class Distance Ratio: A Feature Filtering Metric for Image Classification”, Neurocomputing, vol. 165, pp. 211–221, Oct. 2015.

P. Peng, L. Shao, J. Han and J. Han, “Saliency-Aware Image-to-Class Distances for Image Classification”, Neurocomputing, vol. 166, pp. 337–345, Oct. 2015.

L. Shao, F. Zhu and X. Li, “Transfer Learning for Visual Categorization: A Survey”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 5, pp. 1019-1034, May 2015.

L. Liu, M. Yu and L. Shao, “Multiview Alignment Hashing for Efficient Image Search”, IEEE Transactions on Image Processing, vol. 24, no. 3, pp. 956-966, Mar. 2015.

K. Lu, N. He, J. Xue, J. Dong and L. Shao, “Learning View-Model Joint Relevance for 3D Object Retrieval”, IEEE Transactions on Image Processing, vol. 24, no. 5, pp. 1449 – 1459, May 2015.

R. A. Manap and L. Shao, “Non-Distortion-Specific No-Reference Image Quality Assessment: A Survey”, Information Sciences, vol. 301, pp. 141–160, Apr. 2015.

Q. Zhu, L. Shao, X. Li and L. Wang, “Targeting Accurate Object Extraction From an Image: A Comprehensive Study of Natural Image Matting”, IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 2 pp. 185-207, Feb. 2015.

X. Ji, J. Han, X. Ji, X. Hu, L. Guo, J. Han, L. Shao and T. Liu, “Analysis of Music/Speech via Integration of Audio Content and Functional Brain Response”, Information Sciences, vol. 297, pp. 271–282, Mar. 2015.

X. Wen, L. Shao, W. Fang and Y. Xue, “A Rapid Learning Algorithm for Vehicle Classification”, Information Sciences, vol. 295, pp. 395–406, Feb. 2015.

J. Han, C. Chen, L. Shao, X. Hu, J. Han and T. Liu, “Learning Computational Models of Video Memorability from fMRI Brain Imaging”, IEEE Transactions on Cybernetics, vol. 45, no. 8, pp. 1692-1703, Aug. 2015.

X. Wen, L. Shao, W. Fang and Y. Xue, “Efficient Feature Selection and Classification for Vehicle Detection”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 3, pp. 508-517, Mar. 2015.

L. Liu, L. Shao and F. Zheng and X. Li, “Realistic Action Recognition via Sparsely-Constructed Gaussian Processes”, Pattern Recognition, vol. 47, no. 12, pp. 3819-3827, Dec. 2014.

J. Han, L. Sun, X. Hu, J. Han and L. Shao, “Spatial and Temporal Visual Attention Prediction in Videos Using Eye Movement Data”, Neurocomputing, vol. 145, pp. 140-153, Dec. 2014.

L. Zhang, X. Zhen and L. Shao, “Learning Object-to-Class Kernels for Scene Classification”, IEEE Transactions on Image Processing, vol. 23, no. 8, pp. 3241-3253, Aug. 2014.

X. Zhen, L. Shao and X. Li, “Action Recognition by Spatio-Temporal Oriented Energies”, Information Sciences, vol. 281, pp. 295-309, Oct. 2014. [Impact Factor: 3.893] [Code]

F. Zhu and L. Shao, Weakly-Supervised Cross-Domain Dictionary Learning for Visual Recognition”, International Journal of Computer Vision (IJCV), vol. 109, no. 1-2, pp. 42-59, Aug. 2014. [Code]

L. Shao, D. Wu and X. Li, Learning Deep and Wide: A Spectral Method for Learning Deep Networks”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 12, pp. 2303-2308, Dec. 2014. [Top 1 Most Frequently Downloaded Paper of TNNLS in Dec. 2014]

J. Tang, L. Shao and X. Li, “Efficient Dictionary Learning for Visual Categorization”, Computer Vision and Image Understanding, vol. 124, pp. 91-98, Jul. 2014.

J. Li, W. Huang, L. Shao and N. Allinson, “Building Recognition in Urban Environments: A Survey of State-of-the-Art and Future Challenges Information Sciences, vol. 277, pp. 406-420, Sep. 2014.

A. Khan, A. Jaffar and L. Shao, “A Modified Adaptive Differential Evolution Algorithm for Color Image Segmentation”, Knowledge and Information Systems, vol. 43, no. 4, pp. 583-597, Jun. 2015.

J. Han, K. Li, L. Shao, X. Hu, S. He, L. Guo, J. Han and T. Liu, “Video Abstraction Based on fMRI-Driven Visual Attention Model”, Information Sciences, vol. 281, pp. 781-796, Oct. 2014.

L. Shao, L. Liu and X. Li, “Feature Learning for Image Classification via Multiobjective Genetic Programming”, IEEE Transactions on Neural Networks and Learning Systems, vol. 25, no. 7, pp. 1359-1371, Jul. 2014. [Impact Factor: 4.370]

L. Shao, X. Gao and H. Li, “Image Restoration and Enhancement: Recent Advances and Applications”, Signal Processing, vol. 103, pp. 1-5, Oct. 2014.

R. Yan, L. Shao, L. Liu and Y. Liu, “Natural Image Denoising Using Evolved Local Adaptive Filters”, Signal Processing, vol. 103, pp. 36-44, Oct. 2014. [Impact Factor: 2.238]

L. Shao, R. Yan, X. Li and Y. Liu, “From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms”, IEEE Transactions on Cybernetics, vol. 44, no. 7, pp. 1001-1013, Jul. 2014.

J. Tang, L. Shao and X. Zhen, “Robust Point Pattern Matching Based on Spectral Context”, Pattern Recognition, vol. 47, no. 3, pp. 1469-1484, Mar. 2014.

J. Han, D. Wang, L. Shao, X. Qian, G. Cheng and J. Han, “Image Visual Attention Computation and Application via The Learning of Object Attributes”, Machine Vision and Applications, vol. 25, no. 7, pp. 1671-1683, Oct. 2014.

R. Yan, L. Shao and Y. Liu, “Nonlocal Hierarchical Dictionary Learning Using Wavelets for Image Denoising”, IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 4689-4698, Dec. 2013.

L. Shao and A. U. Rehman, “Image Demosaicing Using Content and Colour-Correlation Analysis”, Signal Processing, vol. 103, pp. 84-91, Oct. 2014.

L. Shao, X. Zhen, D. Tao and X. Li, “Spatio-Temporal Laplacian Pyramid Coding for Action Recognition”, IEEE Transactions on Cybernetics, vol. 44, no. 6, pp. 817-827, Jun. 2014. [Code]

L. Shao, S. Jones and X. Li, “Efficient Search and Localization of Human Actions in Video Databases”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 3, pp. 504-512, Mar. 2014.

L. Shao, J. Han, D. Xu and J. Shotton, “Computer Vision for RGB-D Sensors: Kinect and Its Applications”, IEEE Transactions on Cybernetics, vol. 43, no. 5, pp. 1313-1316, Oct. 2013.

J. Han, L. Shao, D. Xu and J. Shotton, “Enhanced Computer Vision with Microsoft Kinect Sensor: A Review”, IEEE Transactions on Cybernetics, vol. 43, no. 5, pp. 1317-1333, Oct. 2013. [Top 1 Most Frequently Downloaded Paper of T-CYB in 2013-2016]

S. Jones and L. Shao, “Content-Based Retrieval of Human Actions from Realistic Video Databases”, Information Sciences, vol. 236, pp. 56-65, Jul. 2013.

L. Liu, L. Shao, X. Zhen and X. Li, “Learning Discriminative Key Poses for Action Recognition”, IEEE Transactions on Cybernetics, vol. 43, no. 6, pp. 1860-1870, Dec. 2013. (Previously Known as: IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics) [Impact Factor: 3.781]

D. Wu and L. Shao, Multi-Max-Margin Support Vector Machine for Multi-Source Human Action Recognition”, Neurocomputing, vol. 127, pp. 98-103, Mar. 2014. [Impact Factor: 2.005]

S. Jones, L. Shao and K. Du, “Active Learning for Human Action Retrieval Using Query Pool Selection”, Neurocomputing, vol. 124, pp. 89-96, Jan. 2014.

D. Guo, L. Shao and J. Han, “Feature-Based Motion Compensated Interpolation for Frame Rate Up-Conversion”, Neurocomputing, vol. 123, pp. 390-397, Jan. 2014.

X. Zhen and L. Shao, “A Local Descriptor Based on Laplacian Pyramid Coding for Action Recognition”, Pattern Recognition Letters, vol. 34, no. 15, pp. 1899-1905, Nov. 2013.

D. Zhao, L. Shao, X. Zhen and Y. Liu, “Combining Appearance and Structural Features for Human Action Recognition”, Neurocomputing, vol. 113, pp. 88-96, Aug. 2013.

X. Zhen, L. Shao, D. Tao and X. Li, “Embedding Motion and Structure Features for Human Action Recognition”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 7, pp. 1182-1190, Jul. 2013.

L. Liu, L. Shao and P. Rockett, “Boosted Key-Frame Selection and Correlated Pyramidal Motion-Feature Representation for Human Action Recognition”, Pattern Recognition, vol. 46, no. 7, pp. 1810-1818, Jul. 2013.

F. Zheng, Z. Song, L. Shao, R. C. Chung, K. Jia and X. Wu, “A Semi-Supervised Approach for Dimensionality Reduction with Distributional Similarity”, Neurocomputing, vol. 103, pp. 210-221, Mar. 2013.

L. Liu, L. Shao and P. Rockett, “Human Action Recognition Based on Boosted Feature Selection and Naïve Bayes Nearest-Neighbor Classification”, Signal Processing, vol. 93, no. 6, pp. 1521-1530, Jun. 2013.

D. Wu and L. Shao, “Silhouette Analysis-Based Action Recognition Via Exploiting Human Poses”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 2, pp. 236-243, Feb. 2013.

F. Zhu, L. Shao and M. Lin, “Multi-View Action Recognition Using Local Similarity Random Forests and Sensor Fusion”, Pattern Recognition Letters, vol. 34, no. 1, pp. 20-24, Jan. 2013.

M. Mubashir, L. Shao and L. Seed, “A Survey on Fall Detection: Principles and Approaches”, Neurocomputing, vol. 100, pp. 144-153, Jan. 2013.

R. Hong and L. Shao, “Learning from Social Media Network”, Neurocomputing, vol. 95, Oct. 2012.

R. Yan, L. Shao, S. D. Cvetkovic and J. Klijn, “Improved Nonlocal Means Based on Pre-Classification and Invariant Block Matching”, IEEE/OSA Journal of Display Technology, vol. 8, no. 4, pp. 212-218, Apr. 2012.

A. U. Rehman and L. Shao, “Classification-Based De-Mosaicing for Digital Cameras”, Neurocomputing, vol. 83, pp. 222-228, Apr. 2012.

L. Shao, L. Ji, Y. Liu and J. Zhang, “Human Action Segmentation and Recognition via Motion and Shape Analysis”, Pattern Recognition Letters, vol. 33, no. 4, pp. 438-445, Mar. 2012. [Most Downloaded Article of PRL in 2013]

S. Jones, L. Shao, J. Zhang and Y. Liu, “Relevance Feedback for Real World Human Action Retrieval”, Pattern Recognition Letters, vol. 33, no. 4, pp. 446-452, Mar. 2012.

L. Shao, Q. Tian, A. Bimbo and C. Xu, “Intelligent Multimedia Interactivity”, Pattern Recognition Letters, vol. 33, no. 4, Mar. 2012.

H. Yang, L. Shao, F. Zheng, L. Wang and Z. Song, “Recent Advances and Trends in Visual Tracking: A Review”, Neurocomputing, vol. 74, no. 18, pp. 3823-3831, Nov. 2011.

L. Shao, X. Zhen, Y. Liu and L. Ji, “Human Action Representation Using Pyramid Correlogram of Oriented Gradients on Motion History Images”, International Journal of Computer Mathematics, vol. 88, no. 18, pp. 3882-3895, Dec. 2011.

F. Zheng, L. Shao, Z. Song and X. Chen, “Action Recognition Using Graph Embedding and the Co-occurrence Matrices Descriptor”, International Journal of Computer Mathematics, vol. 88, no. 18, pp. 3896-3914, Dec. 2011.

L. Shao, R. Gao, Y. Liu and H. Zhang, “Transform Based Spatio-Temporal Descriptors for Human Action Recognition”, Neurocomputing, vol. 74, no. 6, pp. 962-973, Feb. 2011.

L. Shao, H. Zhang, L. Wang and L. Wang, “Repairing Imperfect Video Enhancement Algorithms Using Classification-Based Trained Filters”, Signal, Image and Video Processing, vol. 5, no. 3, pp. 307-313, Sep. 2011.

L. Shao, J. E. Caviedes, K. Ma and E. B. Bellers, “Video Restoration and Enhancement: Algorithms and Applications”, Signal, Image and Video Processing, vol. 5, no. 3, Sep. 2011.

L. Shao, J. Wang, I. Kirenko and G. de Haan, “Quality Adaptive Least Squares Filters for Compression Artifacts Removal Using a No-reference Block Visibility Metric”, Journal of Visual Communication and Image Representation, vol. 22, no. 1, pp. 23-32, Jan. 2011.

J. Han, L. Shao, P. H. N. de With and L. Guan, “Video Analysis, Abstraction and Retrieval: Techniques and Applications”, International Journal on Digital Multimedia Broadcasting, vol. 2010, Article ID 348914, 2010. 

L. Shao, H. Zhang, K. K. Wong and J. Luo, “Fast and Robust Methods for Multiple-View Vision”, EURASIP Journal on Image and Video Processing, vol. 2010, Article ID 205283, 2010.

I. Djurovic, L. Stankovic, M. Rupp and L. Shao, “Robust Processing of Nonstationary Signals”, EURASIP Journal on Advances in Signal Processing, vol. 2010, Article ID 724746, 2010.

L. Shao, H. Zhang and G. de Haan, “An Overview and Performance Evaluation of Classification Based Least Squares Trained Filters”, IEEE Transactions on Image Processing, vol. 17, no. 10, pp. 1772-1782, Oct. 2008.

L. Shao, “Simultaneous Coding Artifact Reduction and Sharpness Enhancement for Block-based Compressed Images and Videos”, Signal Processing: Image Communication, vol. 23, no. 6, pp. 463-470, Jul. 2008.

L. Shao, “Up-scaling Images in Presence of Salt and Pepper Noise”, IET Electronics Letters, vol. 43, no. 14, pp. 746-748, Jul. 2007.

L. Shao and I. Kirenko, “Coding Artifact Reduction Based on Local Entropy Analysis”, IEEE Transactions on Consumer Electronics, vol. 53, no. 2, pp. 691-696, May 2007.

L. Shao, “Adaptive Resolution Upconversion for Compressed Video Using Pixel Classification”, EURASIP Journal on Advances in Signal Processing, Special Issue on Super-Resolution Enhancement of Digital Video, vol. 2007, Article ID 71432, 2007.

L. Shao, “Unified Compression Artifacts Removal Based on Adaptive Learning on Activity Measure”, Digital Signal Processing, vol. 17, no. 6, pp. 1065-1070, Nov. 2007.

I. Kirenko, R. van der Vleuten and L. Shao, “Optimizing Scalable Video Compression for Efficient Implementation on a VLIW Media Processor”, IEEE Transactions on Multimedia, vol. 9, no. 2, pp. 429-434, Feb. 2007.

L. Shao, “Partial Volume Compensated Reconstruction of Three-dimensional Mass Shapes in Mammographic Images”, Journal of Digital Imaging, vol. 20, no. 2, pp. 191-195, Jun. 2007.

L. Shao and M. Brady, “Invariant Salient Regions Based Image Retrieval under Viewpoint and Illumination Variations”, Journal of Visual Communication and Image Representation, vol. 17, no. 6, pp. 1256-1272, Dec. 2006.

L. Shao, T. Kadir and M. Brady, “Geometric and Photometric Invariant Distinctive Regions Detection”, Information Sciences, vol. 177, no. 4, pp. 1088-1122, Feb. 2007. [Impact Factor: 3.893]

L. Shao and M. Brady, “Specific Object Retrieval Based on Salient Regions”, Pattern Recognition, vol. 39, no. 10, pp. 1932-1948, Oct. 2006.

Book Chapters

X. Zhen and L. Shao, “Introduction to Human Action Recognition”, Wiley Encyclopedia of Electrical and Electronics Engineering, 1–11, 2015.

R. Mattivi and L. Shao, “Robust Spatio-temporal Features for Human Action Recognition”, in W. Lin, D. Tao, J. Kacprzyk, Z. Li, E. Lzquierdo and H. Wang (Eds.), Multimedia Analysis, Processing and Communications, Springer-Verlag, 2011.

L. Shao and R. Gao, “Synthesizing Natural Images Using Spatial Layout Information”, in M. Mrak, M. Grgic and M. Kunt (Eds.), High-quality Visual Experience: Creation, Processing and Interactivity of High-resolution and High-dimensional Video Signals, Springer-Verlag, 2010.

R. Mattivi and L. Shao, “Spatio-temporal Dynamic Texture Descriptors for Human Motion Recognition”, in J. Zhang, L. Shao, L. Zhang and G. Jones (Eds.), Intelligent Video Event Analysis and Understanding, Studies in Computational Intelligence Book Series, Springer-Verlag, 2010.

R. Jin and L. Shao, “Retrieving Human Actions Using Spatio-temporal Features and Relevance Feedback”, in L. Shao, C. Shan, J. Luo and M. Etoh (Eds.), Multimedia Interaction and Intelligent User Interfaces: Principles, Methods and Applications, Springer-Verlag, 2010.

Y. Du and L. Shao, “Efficient Face Retrieval Based on Bag of Facial Features”, in Y-J Zhang (Ed.), Advances in Face Image Analysis: Techniques and Technologies, IGI Global, 2010.

L. Shao, “A Survey on Feature Based Image Retrieval Techniques”, in Z. Ma and L. Yan (Eds.), Intelligent Multimedia Databases and Information Retrieval: Advancing Applications and Technologies, IGI Global, 2010.

Conference Papers

J. Qin, L. Liu, L. Shao, B. Ni, C. Chen, F. Shen and Y. Wang, “Binary Coding for Partial Action Analysis with Limited Observation Ratios”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

L. Liu, L. Shao, F. Shen and M. Yu, “Discretely Coding Semantic Rank Orders for Supervised Image Hashing”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

Y. Long, L. Liu, L. Shao, F. Shen, G. Ding and J. Han, “From Zero-Shot Learning to Conventional Supervised Classification: Unseen Visual Data Synthesis”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

J. Qin, L. Liu, L. Shao, F. Shen, B. Ni, J. Chen and Y. Wang, “Zero-Shot Action Recognition with Error-Correcting Output Codes”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

L. Liu, F. Shen, Y. Shen, X. Liu and L. Shao, “Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017. [Spotlight Paper]

J. Chen, Y. Wang, J. Qin, L. Liu and L. Shao, “Fast Person Re-Identification via Cross-Camera Semantic Binary Transformation”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

Y. Huang, L. Shao and A. Frangi, “Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA, 2017.

L. Liu, Y. Zhou and L. Shao, “DAP3D-Net: Where, What and How Actions Occur in Videos?”, IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

Y. Shen, L. Zhang and L. Shao, “Semi-Supervised Vision-Language Mapping via Variational Learning”, IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.

Y. Long and L. Shao, “Describing Unseen Classes by Exemplars: Zero-shot Learning Using Grouped Simile Ensemble”, IEEE Winter Conference on Applications of Computer Vision (WACV), Santa Rosa, USA, 2017. 

Y. Long, L. Liu and L. Shao, “Towards Fine-grained Open Zero-shot Learning: Inferring Unseen Visual Features from Attributes”, IEEE Winter Conference on Applications of Computer Vision (WACV), Santa Rosa, USA, 2017.

Y. Zhou, L. Liu, L. Shao and M. Mellor, “DAVE: A Unified Framework for Fast Vehicle Detection and Annotation”, European Conference on Computer Vision (ECCV), Amsterdam, The Netherlands, 2016. [Dataset]

C. Lee and L. Shao, “Learning-Based Single Image Dehazing via Genetic Programming”, International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 2016.

Y. Long, L. Liu and L. Shao, “Attribute Embedding with Visual-Semantic Ambiguity Removal for Zero-shot Learning”, British Machine Vision Conference (BMVC), York, UK, 2016.

F. Zheng and L. Shao, “Learning Cross-view Binary Identities for Fast Person Re-identification”, International Joint Conference on Artificial Intelligence (IJCAI), New York, USA, July 2016.

Y. Huang, F. Zhu, L. Shao and A. Frangi, “Color Object Recognition via Cross-Domain Learning on RGB-D Images”, IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

J. Zhang, L. Zhang, H. Shum and L. Shao, “Arbitrary View Action Recognition via Transfer Dictionary Learning on Synthetic Training Data”, IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016.

L. Liu, M. Yu and L. Shao, “Projection Bank: From High-dimensional Data to Medium-length Binary Codes”, IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, Dec. 2015.

R. A. Manap, A. F. Frangi and L. Shao, “A Non-Parametric Framework for No-Reference Image Quality Assessment”, IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, USA, 2015.

S. Tan, F. Zheng and L. Shao, “Dense Invariant Feature Based Support Vector Ranking for Person Re-identification”, IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, USA, 2015.

R. A. Manap, A. F. Frangi and L. Shao, “Blind Image Quality Assessment via A Two-Stage Non-Parametric Framework”, IAPR Asian Conference on Pattern Recognition (ACPR), Kuala Lumpur, Malaysia, 2015.

Z. Cai, L. Liu, M. Yu and L. Shao, “Latent Structure Preserving Hashing”, British Machine Vision Conference (BMVC), Swansea, UK, 2015. [Oral – Acceptance Rate: 7%]

L. Liu, M. Yu and L. Shao, “Local Feature Binary Coding for Approximate Nearest Neighbor Search”, British Machine Vision Conference (BMVC), Swansea, UK, 2015. [Oral – Acceptance Rate: 7%]

J. Qin, L. Liu, M. Yu, Y. Wang and L. Shao, “Fast Action Retrieval from Videos via Feature Disaggregation”, British Machine Vision Conference (BMVC), Swansea, UK, 2015. [Oral – Acceptance Rate: 7%]

B. Dong, L. Shao, M. D. Costa, O. Bandmann and A. F. Frangi, Deep Learning for Automatic Cell Detection in Wide-field Microscopy Zebrafish Images”, IEEE International Symposium on Biomedical Imaging (ISBI), 2015. [Oral]

F. Zhu, L. Shao and M. Yu, “Cross-Modality Submodular Dictionary Learning for Information Retrieval, ACM International Conference on Information and Knowledge Management (CIKM), Shanghai, China, 2014. [Oral]

D. Wu and L. Shao, “Multimodal Dynamic Networks for Gesture Recognition”, ACM International Conference on Multimedia (MM), Orlando, USA, 2014.

F. Zheng, L. Shao, J. Brownjohn and V. Racic “Learn++ for Robust Object Tracking”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014. [Oral – Acceptance Rate: 7.7%]

X. Zhen, L. Shao and F. Zheng, “Discriminative Embedding via Image-to-Class Distances”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014. [Oral – Acceptance Rate: 7.7%] 

F. Zhu, L. Shao and J. Tang, “Boosted Cross-Domain Categorization”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014. [Oral – Acceptance Rate: 7.7%]

Q. Zhu, J. Mai and L. Shao, “Single Image Dehazing Using Color Attenuation Prior”, British Machine Vision Conference (BMVC), Nottingham, UK, 2014.

D. Wu and L. Shao, “Deep Dynamic Neural Networks for Gesture Segmentation and Recognition”, ECCV ChaLearn Looking at People Workshop, Zurich, Switzerland, 2014.

F. Zhu and L. Shao, “Correspondence-Free Dictionary Learning for Cross-View Action Recognition”, International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014.

X. Zhen and L. Shao, “A Performance Evaluation on Action Recognition with Local Features”, International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014.

L. Liu and L. Shao, “Discriminative Partition Sparsity Analysis”, International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014.

B. Dong, L. Shao, A. F. Frangi, O. Bandmann, M. D. Costa, “Three-Dimensional Deconvolution of Wide Field Microscopy with Sparse Priors: Application to Zebrafish Imagery”, International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 2014.

S. Jones and L. Shao, “Unsupervised Spectral Dual Assignment Clustering of Human Actions in Context”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014. [Oral – Acceptance Rate: 5.75%] [Code]

S. Jones and L. Shao, “A Multigraph Representation for Improved Unsupervised/Semi-supervised Learning of Human Actions”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014. [Code]

F. Zhu, Z. Jiang and L. Shao, “Submodular Object Recognition”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014.

D. Wu and L. Shao, “Leveraging Hierarchical Parametric Networks for Skeletal Joints Based Action Segmentation and Recognition”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2014.

S. Jones and L. Shao, “Linear Regression Motion Analysis for Unsupervised Temporal Segmentation of Human Actions”, IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, USA, 2014.

J. Tang and L. Shao and S. JonesPoint Pattern Matching Based on Line Graph Spectral Context and Descriptor Embedding”, IEEE Winter Conference on Applications of Computer Vision (WACV), Steamboat Springs, USA, 2014.

L. Liu, L. Shao and X. Li, “Building Holistic Descriptors for Scene Recognition: A Multi-objective Genetic Programming Approach”, ACM International Conference on Multimedia (MM), Barcelona, Spain, 2013. [Full Paper: Oral]

J. Luo, C. Shan, L. Shao and M. Etoh, “The Third ACM International Workshop on Interactive Multimedia on Mobile and Portable Devices (IMMPD'13)”, ACM International Conference on Multimedia (MM), Barcelona, Spain, 2013.

F. Zhu and L. Shao, “Enhancing Action Recognition by Cross-Domain Dictionary Learning”, British Machine Vision Conference (BMVC), Bristol, UK, 2013. [Oral – Acceptance Rate: 7%]

R. Yan and L. Shao, “Image Blur Classification and Parameter Identification Using Two-stage Deep Belief Networks”, British Machine Vision Conference (BMVC), Bristol, UK, 2013.

J. Tang, L. Shao and X. Zhen, “Human Action Retrieval via Efficient Feature Matching”, IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), Krakow, Poland, 2013.

S. Jones and L. Shao, “Rapid Localisation and Retrieval of Human Actions with Relevance Feedback”, International Conference on Computer Analysis of Images and Patterns (CAIP), York, UK, 2013.

L. Liu and L. Shao, “Learning Discriminative Representations from RGB-D Video Data”, International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013. [Dataset]

L. Liu and L. Shao, “Synthesis of Spatio-Temporal Descriptors for Dynamic Hand Gesture Recognition Using Genetic Programming”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), Shanghai, China, 2013.

X. Zhen and L. Shao, “Spatio-Temporal Steerable Pyramid for Human Action Recognition”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), Shanghai, China, 2013.

Q. Zhu, L. Shao, Z. Song and Y. Xie, “SUPERCUT: An Accurate and Effective Interactive Image Segmentation Algorithm”, IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, 2013.

Q. Zhu, R. Ye, L. Shao, Q. Li and Y. Xie, “A Novel Thin Elongated Objects Segmentation Based on Fuzzy Connectedness and GMM Learning”, IEEE International Conference on Image Processing (ICIP), Melbourne, Australia, 2013.

Q. Zhu, L. Shao, Q. Li and Y. Xie, “Recursive Kernel Density Estimation for Modeling the Background and Segmenting Moving Objects”, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, 2013.

Q. Zhu, L. Shao, Q. Li and Y. Xie, “Perfect Snapping”, International Conference on Multimedia Modeling (MMM), Huangshan, China, 2013.

L. Liu, L. Shao and P. Rockett, “Genetic Programming-Evolved Spatio-Temporal Descriptor for Human Action Recognition”, British Machine Vision Conference (BMVC), Surrey, UK, 2012.

L. Shao, C. Shan and M. Etoh, “The Second ACM International Workshop on Interactive Multimedia on Mobile and Portable Devices”, ACM International Conference on Multimedia (MM), Nara, Japan, 2012.

D. Wu, F. Zhu, L. Shao and H. Zhang, “One Shot Learning Gesture Recognition with Kinect Sensor”, ACM International Conference on Multimedia (MM), Nara, Japan, 2012.

H. Zhang, L. Shao and K. K. Wong, “Self-calibration and Motion Recovery from Silhouettes with Two Mirrors”, Asian Conference on Computer Vision (ACCV), Daejeon, Korea, 2012.

L. Zhang, X. Zhen and L. Shao, “High Order Co-Occurrence of Visual Words for Action Recognition”, IEEE International Conference on Image Processing (ICIP), Orlando, USA, 2012.

D. Wu, F. Zhu and L. Shao, “One Shot Learning Gesture Recognition from RGBD Images”, CVPR 2012 Workshop on Gesture Recognition, Providence, USA, 2012.

J. Luo, C. Shan, L. Shao and M. Etoh, “ACM International Workshop on Interactive Multimedia on Mobile and Portable Devices (IMMPD’11)”, ACM International Conference on Multimedia (MM), Scottsdale, USA, 2011.

L. Shao, D. Wu and X. Chen, “Action Recognition Using Correlogram of Body Poses and Spectral Regression”, IEEE International Conference on Image Processing (ICIP), Brussels, Belgium, September 2011.

S. Jones and L. Shao, “Action Retrieval with Relevance Feedback on YouTube Videos”, ACM International Conference on Internet Multimedia Computing and Service (ICIMCS), Chengdu, China, August 2011.

S. Zhong, Y. Liu, L. Shao and G. Wu, “Unsupervised Saliency Detection Based on 2D Gabor and Curvelet Transforms”, ACM International Conference on Internet Multimedia Computing and Service (ICIMCS), Chengdu, China, August 2011.

S. Zhong, Y. Liu, L. Shao and F. Chung, “Water Reflection Recognition via Minimizing Reflection Cost Based on Motion Blur Invariant Moments”, ACM International Conference on Multimedia Retrieval (ICMR), Trento, Italy, April 2011.

L. Shao, H. Zhang and Y. Liu, “A Generalized Coding Artifacts and Noise Removal Algorithm for Digitally Compressed Video Signals”, International Conference on Multimedia Modelling (MMM), Taipei, Taiwan, January 2011.

C. Li, L. Shao, C. Xu and H. Lu, “Feature Selection under Learning to Rank Model for Multimedia Retrieve”, ACM International Conference on Internet Multimedia Computing and Service (ICIMCS), Harbin, China, December 2010.

L. Shao and X. Chen, “Histogram of Body Poses and Spectral Regression Discriminant Analysis for Human Action Categorization”, British Machine Vision Conference (BMVC), Aberystwyth, UK, August-September 2010.

L. Shao and R. Gao, “A Wavelet Based Local Descriptor for Human Action Recognition”, British Machine Vision Conference (BMVC), Aberystwyth, UK, August-September 2010.

L. Shao and R. Jin, “Subspace Learning for Silhouette Based Human Action Recognition”, SPIE International Conference on Visual Communication and Image Processing (VCIP), Huang Shan, China, July 2010.

L. Shao and R. Mattivi, “Feature Detector and Descriptor Evaluation in Human Action Recognition”, ACM International Conference on Image and Video Retrieval (CIVR), Xi’an, China, July 2010.

L. Shao and L. Ji, “A Descriptor Combining MHI and PCOG for Human Motion Classification”, ACM International Conference on Image and Video Retrieval (CIVR), Xi’an, China, July 2010.

F. Zheng, L. Shao and Z. Song, “A Set of Co-occurrence Matrices on the Intrinsic Manifold of Human Silhouettes for Action Recognition”, ACM International Conference on Image and Video Retrieval (CIVR), Xi’an, China, July 2010.

F. Zheng, L. Shao and Z. Song, “Eigen-space Learning Using Semi-supervised Diffusion Maps for Human Action Recognition”, ACM International Conference on Image and Video Retrieval (CIVR), Xi’an, China, July 2010.

L. Shao, C. Shan, J. Luo and M. Etoh, “1st ACM International Workshop on Interactive Multimedia for Consumer Electronics (IMCE’09)”, ACM International Conference on Multimedia (MM), Beijing, China, 2009.

L. Shao and Y. Du, “Spatio-temporal Shape Contexts for Human Action Retrieval”, ACM International Workshop on Interactive Multimedia for Consumer Electronics (IMCE), Beijing, China, October 2009.

Y. Du and L. Shao, “Video Shots Retrieval Using Local Invariant Features”, ACM International Workshop on Interactive Multimedia for Consumer Electronics (IMCE), Beijing, China, October 2009.

R. Mattivi and L. Shao, “Human Action Recognition Using LBP-TOP as Sparse Spatio-temporal Feature Descriptor”, International Conference on Computer Analysis of Images and Patterns (CAIP), Munster, Germany, September 2009.

R. Gao and L. Shao, “Projected Orthogonal Shape Contexts for Human Action Description and Categorization”, ACCV International Workshop on Video Event Categorization, Tagging and Retrieval (VECTaR), Xi’an, China, September 2009.

H. Wang and L. Shao, “Trimmed Optical Flow Using Localized Region-Based Active Contour”, ACCV Workshop on Vision Based Human Modeling and Synthesis in Motion and Expression, Xi’an, China, September 2009.

L. Shao and L. Ji, “Motion Histogram Analysis Based Key Frame Extraction for Human Action/Activity Representation”, the 6th Canadian Conference on Computer and Robot Vision (CRV), Kelowna, Canada, May 2009.

L. Shao, “An Efficient Local Invariant Region Detector for Image Retrieval”, the 6th Canadian Conference on Computer and Robot Vision (CRV), Kelowna, Canada, May 2009.

L. Shao, I. Kirenko, A. Leitao and P. Mydlowski, “Motion-compensated Techniques for Enhancement of Low Quality Compressed Videos”, the 34th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Taibei, Taiwan, April 2009.

P. Li, L. Shao and D. Znamenskiy, “Block-based Content-adaptive Sharpness Enhancement”, the 13th IEEE International Symposium on Consumer Electronics (ISCE), Kyoto, Japan, May 2009.

H. Zhang, L. Shao and K. K. Wong, “Motion Recovery for Uncalibrated Turntable Sequences Using Silhouettes and a Single Point”, Advanced Concepts for Intelligent Vision Systems (ACIVS), Juan-les-Pins, France, October 2008.

L. Shao, J. Wang, I. Kirenko and G. de Haan, “Quality Adaptive Trained Filters for Compression Artifacts Removal”, the 33rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, USA, March-April 2008.

I. Kirenko, L. Shao, R. Muijs, “Enhancement of Compressed Video Signals Using a Local Blockiness Metric”, the 33rd IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Las Vegas, USA, March-April 2008.

I. Kirenko, L. Shao and A. Nakonechny, “Quality Enhancement of Compressed Video Signals”, the 26th IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, USA, January 2008.

L. Shao, “A Frequency Bands Reconstruction Algorithm for Video Signal Enhancement”, Philips/NXP Joint Conference on Digital Signal Processing (DSP), Veldhoven, Netherlands, February 2008.

L. Shao, H. Hu and G. de Haan, “Coding Artifacts Robust Resolution Up-conversion”, the 14th IEEE International Conference on Image Processing (ICIP), San Antonio, Texas, USA, September 2007.

I. Kirenko and L. Shao, “Adaptive Repair of Compressed Video Signals Using Local Objective Metrics of Blocking Artifacts”, the 14th IEEE International Conference on Image Processing (ICIP), San Antonio, Texas, USA, September 2007.

L. Shao and H. van der Heijden, “Integrated Image Enhancement and Artifacts Reduction Based on Frequency Bands Manipulation”, the 8th IEEE International Conference on Multimedia and Expo (ICME), Beijing, China, July 2007.

L. Shao and M. Zhao, “Order Statistic Filters for Image Interpolation”, the 8th IEEE International Conference on Multimedia and Expo (ICME), Beijing, China, July 2007.

I. Kirenko and L. Shao, “Local Objective Metrics of Blocking Artifacts Visibility for Adaptive Repair of Compressed Video Signals”, the 8th IEEE International Conference on Multimedia and Expo (ICME), Beijing, China, July 2007.

L. Shao and I. Kirenko, “Content Adaptive Coding Artifact Reduction for Decompressed Video and Images”, the 25th IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, USA, January 2007.

L. Shao, “Specific Object and Object Category Retrieval Using Invariant Informative Regions”, the 3rd Philips Symposium on Intelligent Algorithms (SOIA), Eindhoven, The Netherlands, December 2006.

I. Kirenko, R. Muijs and L. Shao, “Coding Artifact Reduction Using Non-reference Block Grid Visibility Measure”, the 7th IEEE International Conference on Multimedia & Expo (ICME), Toronto, Canada, July 2006.

L. Shao, I. Kirenko and P. Li, “Feature Classification Based on Local Information”, the 14th European Signal Processing Conference (EUSIPCO), Florence, Italy, September 2006.

L. Shao, P. Li and I. Kirenko, “Object Category Retrieval for Multimedia Databases”, the 10th IEEE International Symposium on Consumer Electronics (ISCE), St. Petersburg, Russia, June 2006.

L. Shao, “Generic Feature Extraction for Image/Video Analysis”, the 10th IEEE International Symposium on Consumer Electronics (ISCE), St. Petersburg, Russia, June 2006.

L. Shao, L. Bao and I. Kirenko, “Invariant Discriminative Regions for Image Matching under Viewpoint and Illumination Changes”, IASTED International Conference on Signal and Image Processing (SIP), Honolulu, USA, August 2006.

L. Shao, T. Kadir and M. Brady, “An Invariant Salient Region Detector”, the 9th Irish Machine Vision and Image Processing Conference (IMVIP), Belfast, UK,  August 2005. 

L. Shao, “PDF Estimation Techniques for Salient Region Detection”, the 9th Irish Machine Vision and Image Processing Conference (IMVIP), Belfast, UK,  August 2005.

L. Shao and M. Brady, “Three-Dimensional Mass Reconstruction in Mammography”, the 8th European Conference on Computer Vision (ECCV) Workshop on Computer Vision Approaches to Medical Image Analysis, Prague, Czech Republic, May 2004.