[1]姬晓飞,谢旋,任艳.深度学习的双人交互行为识别与预测算法研究[J].智能系统学报,2020,15(3):484-490.[doi:10.11992/tis.201812029]
 JI Xiaofei,XIE Xuan,REN Yan.Human interaction recognition and prediction algorithm based on deep learning[J].CAAI Transactions on Intelligent Systems,2020,15(3):484-490.[doi:10.11992/tis.201812029]
点击复制

深度学习的双人交互行为识别与预测算法研究

参考文献/References:
[1] RYOO M S. Human activity prediction: Early recognition of ongoing activities from streaming videos[C]//Proceedings of 2011 International Conference on Computer Vision. Barcelona, Spain, 2011: 1036-1043.
[2] XU Kaiping, QIN Zheng, WANG Guolong. Human activities prediction by learning combinatorial sparse representations[C]//Proceedings of 2016 IEEE International Conference on Image Processing. Phoenix, USA, 2016: 724-728.
[3] RAPTIS M, SIGAL L. Poselet key-framing: a model for human activity recognition[C]//Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, USA, 2013: 2650-2657.
[4] KONG Yu, FU Yun. Max-margin action prediction machine[J]. IEEE transactions on pattern analysis and machine intelligence, 2016, 38(9): 1844-1858.
[5] KUNZE K, LUKOWICZ P. Dealing with sensor displacement in motion-based onbody activity recognition systems[C]//Proceedings of the 10th International Conference on Ubiquitous Computing. Seoul, South Korea, 2008: 20-29.
[6] BULLING A, ROGGEN D. Recognition of visual memory recall processes using eye movement analysis[C]//Proceedings of the 13th International Conference on Ubiquitous Computing. New York, USA, 2011: 455-464.
[7] VAN KASTEREN T, NOULAS A, ENGLEBIENNE G, et al. Accurate activity recognition in a home setting[C]//Proceedings of the 10th International Conference on Ubiquitous Computing. Seoul, South Korea, 2008: 1-9.
[8] CHUNG P C, LIU C D. A daily behavior enabled hidden Markov model for human behavior understanding[J]. Pattern recognition, 2008, 41(5): 1572-1580.
[9] TANG K, LI Feifei, KOLLER D. Learning latent temporal structure for complex event detection[C]//Proceedings of 2012 IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA, 2012: 1025-1257.
[10] LAFFERTY J D, MCCALLUM A, PEREIRA F C N. Conditional random fields: probabilistic models for segmenting and labeling sequence data[C]//Proceedings of the 18th International Conference on Machine Learning. San Francisco, USA, 2001: 282-289.
[11] ZHANG Jianguo, GONG Shaogang. Action categorization with modified hidden conditional random field[J]. Pattern recognition, 2010, 43(1): 197-203.
[12] SONG Yale, MORENCY L P, DAVIS R. Action recognition by hierarchical sequence summarization[C]//IEEE Conference on Computer Vision and Pattern Recognition. Portland, USA, 2013: 3563-3569.
[13] KE Qiuhong, BENNAMOUN M, AN Senjian, et al. Human interaction prediction using deep temporal features [C]//Proceedings of European Conference on Computer Vision. Amsterdam, The Netherlands, 2016: 403-414.
[14] SIMONYAN K, ZISSERMAN A. Two-stream convolutional networks for action recognition in videos[C]//Proceedings of the 27th International Conference on Neural Information Processing Systems. Montreal, Canada, 2014: 568-576.
[15] HOCHREITER S, SCHMIDHUBER J. Long short-term memory[J]. Neural computation, 1997, 9(8): 1735-1780.
[16] BACCOUCHE M, MAMALET F, WOLF C, et al. Sequential deep learning for human action recognition[C]//Proceedings of the 2nd International Workshop on Human Behavior Understanding. Amsterdam, The Netherlands, 2011: 29-39.
[17] SZEGEDY C, LIU Wei, JIA Yangqing, et al. Going deeper with convolutions[C]//Proceedings of 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, USA, 2015: 1-9.
[18] SZEGEDY C, VANHOUCKE V, IOFFE S, et al. Rethinking the inception architecture for computer vision[C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA, 2016: 2818-2826.
[19] RYOO M S, AGGARWAL J K. Spatio-temporal relationship match: video structure comparison for recognition of complex human activities[C]//Proceedings of 2009 IEEE 12th International Conference on Computer Vision. Kyoto, Japan, 2009: 1593-1600.
相似文献/References:
[1]刘琚,孙建德.独立分量分析的图像/视频分析与应用[J].智能系统学报,2011,6(6):495.
 LIU Ju,SUN Jiande.Independent component analysisbased image/video analysis and applications[J].CAAI Transactions on Intelligent Systems,2011,6(3):495.
[2]梅雪,胡石,许松松,等.基于多尺度特征的双层隐马尔可夫模型及其在行为识别中的应用[J].智能系统学报,2012,7(6):512.
 MEI Xue,HU Shi,XU Songsong,et al.Multi scale feature based double layer HMM and its application in behavior recognition[J].CAAI Transactions on Intelligent Systems,2012,7(3):512.
[3]韩延彬,郭晓鹏,魏延文,等.RGB和HSI颜色空间的一种改进的阴影消除算法[J].智能系统学报,2015,10(5):769.[doi:10.11992/tis.201410010]
 HAN Yanbin,GUO Xiaopeng,WEI Yanwen,et al.An improved shadow removal algorithm based on RGB and HSI color spaces[J].CAAI Transactions on Intelligent Systems,2015,10(3):769.[doi:10.11992/tis.201410010]
[4]申天啸,韩怡园,韩冰,等.基于人类视觉皮层双通道模型的驾驶员眼动行为识别[J].智能系统学报,2022,17(1):41.[doi:10.11992/tis.202106051]
 SHEN Tianxiao,HAN Yiyuan,HAN Bing,et al.Recognition of driver’s eye movement based on the human visual cortex two-stream model[J].CAAI Transactions on Intelligent Systems,2022,17(3):41.[doi:10.11992/tis.202106051]
[5]刘董经典,孟雪纯,张紫欣,等.一种基于2D时空信息提取的行为识别算法[J].智能系统学报,2020,15(5):900.[doi:10.11992/tis.201906054]
 LIU Dongjingdian,MENG Xuechun,ZHANG Zixin,et al.A behavioral recognition algorithm based on 2D spatiotemporal information extraction[J].CAAI Transactions on Intelligent Systems,2020,15(3):900.[doi:10.11992/tis.201906054]

备注/Memo

收稿日期:2018-12-26。
基金项目:国家自然科学基金项目(61602321);辽宁省自然科学基金项目(201602557);辽宁省教育厅科学研究服务地方项目(L201708);辽宁省教育厅科学研究青年项目(L201745)
作者简介:姬晓飞,副教授,博士,主要研究方向为视频分析与处理、模式识别理论。承担国家自然科学基金、辽宁省自然科学基金等多项课题研究。发表学术论文40余篇,参与编著英文专著2部。;谢旋,硕士研究生,主要研究方向为生物特征识别与行为分析技术。;任艳,讲师,博士,主要研究方向为基于公理化模糊集的知识发现与表示、图像语义特征提取。承担国家自然科学基金、航空基金、辽宁省自然科学基金等课题研究。发表学术论文25篇
通讯作者:姬晓飞.E-mail:jixiaofei7804@126.com

更新日期/Last Update: 1900-01-01
Copyright @ 《 智能系统学报》 编辑部
地址:(150001)黑龙江省哈尔滨市南岗区南通大街145-1号楼 电话:0451- 82534001、82518134