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[1] Rui Huang, Hong Cheng, Hongliang Guo, Xichuan Lin, Qiming Chen, Fuchun Sun, Learning Cooperative Primitives with Physical Human-Robot Interaction for a Human-Powered Lower Exoskeleton, IROS, 2016.

[2] Rui Huang, Hong Cheng, Hongliang Guo, Qiming Chen, Xichuan Lin, Hierarchical Interactive Learning for a Human-Powered Augmentation Lower Exoskeleton, In IEEE International Conference on Robotics and Automation, Stockholm, Sweden, 2016(Accepted).

[3] Jianmei Su, Hong Cheng, Lu Yang, Ao Luo, Bayesian View Synthesis For Video Stitching, In ICME Workshop, 2016.

[4] Ling Wang, Hong Cheng, Hai Lan, Yingjie Zheng, Kainan Li, Pertrochanteric Fracture Automatic Recognition with Level Set Approaches, In IEEE Engineering in Medicine and Biology Conference, 2016.

[5] Jing Qiu, Fukui Wang, Long Gao, Hong Cheng, Zhan Li, Intention Recognition of Human Movement Based on EEG, Chinese Control Conference, 2016.

[6] Mien Ka, Hong Cheng, Huu Toan Tran, Qiu Jing, Minimizing Human-Exoskeleton Interaction Force Using Compensation for Dynamic Uncertainty Error with Adaptive RBF Network, Journal of Intelligent and Robotic Systems, Vol. 82, No. 3, pp. 413-433, 2016.

[7] Linxiao Yang, Jun Fang, Hong Cheng, Hongbin Li, Sparse Bayesian learning with a Gaussian hierarchical model, Signal Processing, 2016(Accepted).

[8] Ratha Pech, Dong Hao, Liming Pan, Hong Cheng, Tao Zhou, Link Prediction via Matrix Completion, Social and Information Networks, arXiv:1606.06812, 2016.

[9] Yanxia Zhang, Lu Yang, Binghao Meng, Hong Cheng, Yong Zhang, Qian Wang and Jiadan Zhu,On the Quantitative Analysis of Sparse RBMs, 17th Pacific-Rim Conference on Multimedia (PCM), 2016.

[10] 张良伟,程洪,岳春峰,黄瑞,陈启明。 面向下肢外骨骼机器人的地面特性识别及其系统实现。中国控制会议(CCC),2016。

[11] Dian Huang, Hong Cheng and Lu Yang, Interactive Banknotes Recognition For The Visual Impaired With Wearable Assistive Devices, Chinese Conference on Pattern Recognition, 2016.

[12] Jing Li, Hong Cheng, Runzhou Wang and Lu Yang, Real-time Object Tracking using Dynamic Measurement Matrix, Chinese Conference on Pattern Recognition, 2016.

[13] Kunxia Huang, Chenguang Yang, Hong Cheng, Object Property Identification Using Uncertain Robot Manipulator, Chinese Conference on Pattern Recognition, 2016.

[14] Abusabah I. A. Ahmed, Hong Cheng, Xichuan Lin, Motion Planing and Control of Maneuverable Human-Powered Exoskeleton Systems, in IROS Workshop, 2016.

[15] Yuansheng Luo, Hong Cheng and Lu Yang, Size-Invariant Fully Convolutional Neural Network for Vessel Segmentation of Digital Retinal Images, APSIPA, 2016.


[1] Lu Yang, Hong Cheng, Jianan Su, Xuelong Li, Pixel-to-Model Distance for Robust Background Reconstruction, IEEE Transactions on Circuits and Systerms for Video Technology, 2015.

[2] Huaping Liu, Jie Qin, Hong Cheng, Fuchun Sun, Robust Kernel Dictionary Learning using A Whole Sequence Convergent Algorithm, International Joint Conference on Artificial Intelligence (IJCAI), 2015.

[3] Yang Zhao, Hong Cheng, Lu Yang, 3D Sparse Quantization for Feature Learning In Action Recognition, China SIP, 2015.

[4] Hong Cheng, Lu Yang , Zicheng Liu, A Survey on 3D Hand Gesture Recognition, IEEE Transactions on Circuits and Systerms for Video Technology, 2015.

[5] Nan Zhou, Yangyang Xu, Hong Cheng, Jun Fang, Witold Pedrycz,Global and Local Structure Preserving Sparse Subspace Learning: An Iterative Approach to Unsupervised Feature SelectionPattern Recognition, June 2015(Accepted)

[6] Rui Huang, Hong Cheng, Qiming Chen, HUU TOAN TRAN, Xichuan Lin, Interactive Learning for Sensitivity Factors of a Human-powered Augmentation Lower Exoskeleton, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015

[7] Zhan Li, Hong Cheng, Muscle Synergy Analysis of a Set of Lower Extremity Movements in Quiet Standing Scenario,  IEEE International Conference on Information and Automation 2015 (Oral Paper)

[8] Dekun Hu, Binghao Meng, Shengyi Fan, Hong Cheng, Lu Yang, Yanli Ji, Real-Time Understanding of Abnormal Crowd  Behavior on Social Robots, 16th Pacific-Rim Conference on Multimedia (PCM), 2015

[9] Jingren Tang, Hong Cheng, Lu Yang, Recognizing 3D Continuous Letter Trajectory Gesture Using Dynamic Time Warping,  16th Pacific-Rim Conference on Multimedia (PCM), 2015. (Oral Paper)

[10] Lu Yang, Hong Cheng, Jiasheng Hao, Yanli Ji, Yiqun Kuang, A Survey on Media Interaction in Social Robotics, 16th  Pacific-Rim Conference on Multimedia (PCM), 2015. (Oral Paper)

[11] Ming-Ching Chang, Honggang Qi, Xin Wang, Hong Cheng, Siwei Lyu, Fast online upper body pose estimation from video, British Machine Vision Conference (BMVC), 2015

[12] Toan Huu Tran, Hong Cheng, Rui Huang, Xichuan Lin, Qiming Chen, Evaluation of a fuzzy-based impedance control strategy on a powered lower exoskeleton, International Journal of Social Robotics, 2015

[13] Chengyu Peng, Hong Cheng, Manchor Ko, An Efficient Two-Stage Sparse Representation Method, International Journal of  Pattern Recognition and Artificial Intelligence, 2015

[14] Rui Huang, Hong Cheng, Yi Chen, Xichuan Lin, Jing Qiu, Optimisation of Reference Gait Trajectory of a Lower Limb ExoskeletonInternational Journal of Social Robotics, 2015 (Accepted)

[15] Nan Zhou, Hong Cheng, Huaping Liu, Witold Pedryczb, Discriminative Sparse Subspace Learning and Its Application to Unsupervised Feature Selection, ISA Transactions2015 (Accepted)

[16Hong Cheng, Zhongjun Dai, Zicheng Liu Yang Zhao, An Image-to-Class Dynamic Time Warping Approach for both 3D Static and Trajectory Hand Gesture RecognitionPattern Recognition, Dec. 2015(Accepted)


[1] Ling Wang,  Hong Cheng, Zicheng Liu, Ce Zhu, A Robust Elastic Net Approach for Feature Learning ,

Journal of Visual Communication and Image Representation, Vol. 25, No. 2,  pp. 313-321, February 2014.

[2]Hong Cheng, Rongchao Yu, Zicheng Liu, Lu Yang, Xuewen Chen, Kernelized Pyramid Nearest Neighbor Search for Object Categorization, Machine Vision and Applications, February 2014.

[3] Yali Zheng, Hong Cheng, Yuan Yan Tang, Bin Fang, Optimized Trajectory Recovery of On-road Vehicles from Monocular Videos with Multiple Constraints IEEJ Transactions on Electronics, Information and Systems, Vol. 9,   No. 2, pp.200-206, March 2014.

[4] Hong Cheng, Jun Luo, Xuewen Chen, Windowed Dynamic Time Warping for 3D Hand Trajectory Gesture Recognition, ICME 2014.

[5]Lu Yang, Hong Cheng, Jianan Su, Xuewen Chen, Pixel-to-Model Background Modeling in Crowded Scenes, ICME 2014.

[6]Hong Cheng, Haoyang Zhuang, Yanli Ji, Guo Ye, Yang Zhao, 3D Medial Axis Distance for Hand Detection, ICME Workshop, 2014.

[7]Yanli Ji, Guo Ye, Hong Cheng,  Interactive Body Part Contrast Mining for Human Interaction Recognition, ICME Workshop, 2014.

[8]Huu-Toan Tran, Hong Cheng and Mien-Ka Duong, Learning the Relation of Physical Interaction to Dynamic Factors during Human-Exoskeleton Collaboration,  IEEE International Conference on Multisensor Fusion and Integration, 2014.

[9]Rui Huang, Hong Cheng, Hangming Zheng, Qiming Chen and Xichuan Lin, Study on Master-Slave Control Strategy of Lower Extremity Exoskeleton Robot, WCICA 2014.

[10]Huu-Toan Tran, Hong Cheng, XiChuan Lin, Mien-Ka Duong, Rui Huang, The relationship between physical human-exoskeleton interaction and dynamic factors: using a learning approach for control applications, Science China information Sciences, October 2014.

[11] Y. Wang, H. Cheng, Y. Zheng, L. Yang, Face recognition in the wild by mining frequent feature itemset, CCPR2014.

[12] Wenrong Zeng, Xuewen Chen, Hong Cheng, Pseudo Labels for Imbalanced Multi-Label Learning, DSAA2014.

[13] Melih S. Aslan, Xuewen Chen, Hong Cheng, Learning Sparse and Scale-free Networks, DSAA2014.

[14] Huu Toan Tran, Hong Cheng, Mien Ka Duong and Hangming Zheng, Fuzzy-based Impedance Regulation for Control of the Coupled Human-Exoskeleton System, IEEE ROBIO 2014.


[1] Hong Cheng, Zhongjun Dai,  Zicheng Liu, Image-to-class dynamic time warpping for 3D hand gesture recognition, In IEEE International Conference on Multimedia and Expo, July 2013.[slides]

[2] Yang Zhao, Zicheng Liu, Hong Cheng, RGB-Depth Feature for 3D Human Activity Recognition, China CommunicationVol. 10, No. 7, pp. 93-103, July 2013.

[3] Wenrong Zeng, Xue-Wen Chen, Hong Cheng and Jing Hua, Multi-Space Learning for Image Classification Using AdaBoost and Markov Random FieldsSolving Comeplex Machine Learning Problems with Ensemble Methods  Workshop, 2013.

[4] Hong Cheng, Zicheng Liu, Lu Yang, Xuewen Chen, Sparse Representation and Learning in Visual Recognition: Theory and ApplicationsSignal Processing, Elsevier, Vol. 93, No. 6, pp. 1408-1425, June 2013.

[5]Yiguang Liu, Liping Cao, Chunling Liu, Yifei Pu, Hong Cheng, Recovering Shape and Motion by a Dynamic Systems for Low-rank Matrix Approximation in L1-normVisual ComputerVol. 29, No. 5, pp. 421-431, May 2013.


[1] Hong Cheng, Zicheng Liu, Yang Zhao, Guo Ye, Xinghai Sun, Real World Activity Summary for Senior Home MonitoringMultimedia Tools and Applications, Springer, July  2012.

[2] Hong Cheng, Zicheng Liu, Lei Hou, Jie Yang, Sparsity Induced Similarity and Its Applications,  Circuits and Systems for Video Technology, IEEE Transactions on, Vol. 26, No. 4, pp. 613-626, September, 2012.

[3] Hong Cheng, Zicheng. Liu, Jie Yang. Multi-support-region image descriptors and its application to street landmark localizationMachine Vision and Applications, Vol. 23, No. 4, pp. 805-819, July 2012.

[4] Hong Cheng, Rongchao Yu, Zicheng Liu, Yiguang Liu. A Pyramid Nearest Neighbor Search Kernel for Object Categorization, In IEEE International Conference on Pattern Recognition, 2012.[slides

[5] Ling Wang and Hong Cheng, Robust Sparse PCA via Weighted Elastic Net, In Chinese Conference on Pattern Recognition ,July 2012.

[6] Yiguang Liu, Bingbing Liu, Yifei Pu, Xiaohui Chen, Hong Cheng. Low-rank Matrix Decomposition in L1-norm by Dynamic SystemsImage and Vision Computing, Vol. 30, No. 11, pp. 915-921, July 2012.

[7] Yang Zhao,Zicheng Liu ,Hong Cheng,.Lu Yang. Combing RGB and Depth Map Features for human activity recognitionSignal & Information Processing Association Annual Summit and Conference , 3-6 Dec. 2012


[1] Yali Zheng, et al., Structure from motion blur in low light, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

[2] Hong Cheng, Zicheng Liu, Yang Zhao, Guo Ye. Real World Activity Summary for Senior Home Monitoring. In IEEE International Conference on Multimedia and Expo (ICME), 2011.

[3] 叶果,程洪,赵洋,电影中吸烟活动识别 ,智能系统学报,2011年05期,第六卷,440-444页。


[1] Hong Cheng, Zicheng Liu, Jie Yang. Learning Feature Transforms for Object Detection from Panoramic Images, In IEEE International Conference on Multimedia and Expo (ICME), 2010.


[1] Hong Cheng, Zicheng Liu, Jie Yang. Sparsity Induced Similarity Measure for Label Propagation, In IEEE International Conference on Computer Vision (ICCV), 2009(Oral Paper, 3% accept rate).

[2] Lei Yang, Nanning Zheng, Jie Yang, Mei Chen, Hong Cheng. A Biased Sampling Strategy for Object Categorization, In IEEE International Conference on Computer Vision (ICCV), 2009 (Poster paper, about 20% accept rate).


[1] Hong Cheng, Zicheng Liu, Nanning Zheng, Jie Yang. Deformable Local Image Descriptors, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.


[1] Hong Cheng, Nanning Zheng, Xuetao Zhang, Junjie Qin, Huub van de Wetering. Interactive Road Situation Analysis for Driver Assistance and Safety Warning Systems: Frameworks and Algorithms. In IEEE Transaction on Intelligent Transportation Systems Vol. 8, No. 1, pp. 157-167, March 2007,.

[2] Zhaohui Wu, Qing Wu, Hong Cheng, Gang Pan, Minde Zhao, Jie Sun. ScudWare: A Semantic and Adaptive Middleware Platform for Smart Vehicle Space. In IEEE Transaction on Intelligent Transportation Systems, Vol. 8, No. 1, pp. 121-132, March 2007.

[3] Hong Cheng, Zicheng Liu, Nanning Zheng, Jie Yang. Enhancing a Driver's Situation Awareness using a Global View Map. In International Conference Multimedia Explo 2007: 1019-1022.

[4] Lin Ma, Nanning Zheng, Fan Mu, Yi Dong, Hong Cheng, Yong-Jian He. Geometric and Statistic Constraints in Dynamic Re-orienation of On-board Camera: Inherent Vanishing Points. In IEEE Intelligent Vehicles Symposium, June 2007.


[1] Hong Cheng, Nanning Zheng, Chong Sun, and Huub van de Wetering. Boosted Crucial Gabor Features Applied to Vehicle Detection, In International Conference on Pattern Recognition, August 20-24, 2006, Hong Kong.

[2] Hong Cheng, Nanning Zheng, Chong Sun, and Huub van de Wetering. Vanishing Point and Gabor Feature based Multi-resolution On-Road Vehicle Detection, In International Conference on Neural Networks, May 29-31, 2006}, May 28-31,2006.






Autonomous Intelligent Vehicles




Sparse Representation, Modeling and Learning in Visual Recognition: Theory, Algorithms and Applications