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Learning spatiotemporal representations for human fall detection in surveillance video 期刊论文
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2019, 卷号: 59, 页码: 215-230
作者:  Kong, Yongqiang;  Huang, Jianhui;  Huang, Shanshan;  Wei, Zhengang;  Wang, Shengke
收藏  |  浏览/下载：9/0  |  提交时间：2019/12/11
Video facial emotion recognition based on local enhanced motion history image and CNN-CTSLSTM networks 期刊论文
Journal of Visual Communication and Image Representation, 2019, 卷号: Vol.59, 页码: 176-185
作者:  Min Hu;  Haowen Wang;  Xiaohua Wang;  Juan Yang;  Ronggui Wang
收藏  |  浏览/下载：4/0  |  提交时间：2019/12/13
Learning spatiotemporal representations for human fall detection in surveillance video 期刊论文
JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2019, 卷号: 59, 页码: 215-230
作者:  Kong, Yongqiang;  Huang, Jianhui;  Huang, Shanshan;  Wei, Zhengang;  Wang, Shengke
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/30
Human Actions Recognition Using Improved MHI and 2-D Gabor Filter Based on Energy Blocks 会议论文
作者:  Junfeng Sun;  Hongji Xu;  Yingming Zhou;  Lingling Pan;  Feifei Li
收藏  |  浏览/下载：7/0  |  提交时间：2019/12/31
Robust object tracking based on adaptive templates matching via the fusion of multiple features 期刊论文
Journal of Visual Communication and Image Representation, 2017, 卷号: Vol.44, 页码: 1-20
作者:  Li, Zhiyong;  Gao, Song;  Nai, Ke
收藏  |  浏览/下载：2/0  |  提交时间：2019/12/31
Robust Object Tracking Based on Timed Motion History Image With Multi-feature Adaptive Fusion 会议论文
12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Changsha, PEOPLES R CHINA, AUG 13-15, 2016
作者:  
收藏  |  浏览/下载：6/0  |  提交时间：2019/12/24
基于深度图像的手势交互技术研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院大学, 2014
作者:  秦树鑫
收藏  |  浏览/下载：86/0  |  提交时间：2015/09/02
Efficient human action recognition using accumulated motion image and support vector machines (EI CONFERENCE) 会议论文
International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2011, November 19, 2011 - November 23, 2011, Suzhou, China
Cao W.; Zhang X.; Cao S.; Zhang J.; Wang M.; Han G.
收藏  |  浏览/下载：67/0  |  提交时间：2013/03/25
Vision-based human action recognition provides an advanced interface  and research in this field of human action recognition has been actively carried out. This paper describes a scheme for recognizing human actions from a video sequences. The proposed method is an extension of the Motion History Image(MHI) method based on the ordinal measure of accumulated motion  which is robust to variations of appearances. We define the accumulated motion image(AMI) using image differences firstly. Then the AMI of the video sequencesis resized to a MN regulation following the standard of training phases. Finally  we employ Support Vector Machine(SVM) as a classifier to distinguish the current activity in target video sequences. In a word  our proposed algorithm not only outperforms the state of art on public available KTH data set and Weizmann data set  but also proves practical to some real world applications  in addition  this method is computationally simple and able to achieve a satisfactory accuracy.  
Family Environmental Service Oriented Multiple Object Tracking Based on Multi-cue Method 会议论文
8th World Congress on Intelligent Control and Automation (WCICA), JUL 06-09, 2010
作者:  Yin, Jianqin;  Tian, Guohui;  Xue, Yinghua
收藏  |  浏览/下载：3/0  |  提交时间：2019/12/31
Family environmental service oriented multiple object tracking based on multi-cue method 期刊论文
Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2010, 页码: 6573-6577
作者:  Yin, Jianqin;  Tian, Guohui;  Xue, Yinghua
收藏  |  浏览/下载：2/0  |  提交时间：2019/12/26

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