个人简介
邸慧军,博士,硕士生导师。分别于2002.7和2009.7获清华大学计算机科学与技术专业工学学士和博士学位。2008.2-2009.3在德国慕尼黑西门子公司中央研究所做访问学者,2009.7-2012.7在清华大学计算机科学与技术系从事博士后研究。2012年7月至今在北京理工大学计算机学院从事教学及科研工作。主要研究兴趣包括计算机视觉、人工智能、模式识别、机器学习、智能系统。在计算机领域国际顶级、重要刊物IEEE TPAMI、IEEE TSMCB、IEEE TCSVT、IEEE TMM和国际顶级会议ICCV、CVPR、ECCV上发表学术论文多篇。
研究领域
计算机视觉、人工智能、模式识别、机器学习、智能系统
近期论文
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Qingxuan Shi, Huijun Di, Yao Lu, Feng Lv, and Xuedong Tian. Video Pose Estimation with Global Motion Cues. Neurocomputing, 219:269-279, 2017.
Ying Zhao, Huijun Di, Jian Zhang, Yao Lu, Feng Lv, and Yufang Li. Region Based Mixture Models for Human Action Recognition in Low-Resolution Videos. Neurocomputing, 247:1-15, 2017.
Tianfei Zhou, Yao Lu, and Huijun Di. Locality-Constrained Collaborative Model for Robust Visual Tracking. IEEE Trans. Circuits Syst. Video Techn. (TCSVT), 27(2): 313-325, 2017.
Ming Qin, Yao Lu, Huijun Di, and Wei Huang. A Background Basis Selection Based Foreground Detection Method. IEEE Trans. Multimedia (TMM), 18(7): 1283-1296, 2016.
Huijun Di, Linmi Tao, and Guangyou Xu. A Mixture of Transformed Hidden Markov Models for Elastic Motion Estimation. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 31(10):1817-1830, 2009.
Peng Dai, Huijun Di, Ligeng Dong, Linmi Tao, and Guangyou Xu. Group Interaction Analysis in Dynamic Context. IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics (TSMC-B), 39(1):34-42, 2009.
Ying Zhao, Huijun Di, Jian Zhang, Yao Lu, and Feng Lv. Recognizing Human Actions from Low-Resolution Videos by Region-Based Mixture Models. IEEE International Conference on Multimedia & Expo (ICME), 2016.
Huijun Di, Qingxuan Shi, Feng Lv, Ming Qin, and Yao Lu. Contour Flow: Middle-Level Motion Estimation by Combining Motion Segmentation and Contour Alignment. IEEE International Conference on Computer Vision (ICCV), 2015.
Qifan Wang, Linmi Tao, and Huijun Di. A Globally Optimal Approach for 3D Elastic Motion Estimation from Stereo Sequences. European Conference on Computer Vision (ECCV), 2010
Huijun Di, Naveed Rao, Guangyou Xu, and Linmi Tao. Groupwise Shape Registration on Raw Edge Sequence via A Spatio-Temporal Generative Model. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.