Art

J-GLOBAL ID：201702262600463708   Reference number：17A1224584

Trajectory-Set Feature for Action Recognition

動作認識のための軌道セット特徴

Author (4)： MATSUI Kenji (Hiroshima University) ,  TAMAKI Toru (Hiroshima University) ,  RAYTCHEV Bisser (Hiroshima University) ,  KANEDA Kazufumi (Hiroshima University)
Material： IEICE Transactions on Information and Systems (Web)  (IEICE Trans Inf Syst (Web))
Volume： E100.D  Issue： 8  Page： 1922-1924(J-STAGE)  Publication year： 2017 
JST Material Number： U0469A  ISSN： 1745-1361  Document type： Article
Article type： 短報  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *recognition ,  *orbit (trajectory) ,  set ,  coding (signal) ,  characteristic ,  video recorder ,  Machine Learning ,  Dataset ,  deep learning ,  *motion recognition

Author keywords (3)： action recognition ,  trajectory ,  improved Dense Trajectory

JST classification (1)： Pattern recognition  (JE07000S)

Reference (27)：

• [1] S. Herath, M. Harandi, and F. Porikli, “Going Deeper into Action Recognition: A Survey,” Image and Vision Computing, vol.60, pp.4-21, 2017. 10.1016/j.imavis.2017.01.010
• [2] K. Simonyan and A. Zisserman, “Two-Stream Convolutional Networks for Action Recognition in Videos,” in Advances in Neural Information Processing Systems 27, ed. Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence, and K.Q. Weinberger, pp.568-576, Curran Associates, Inc., 2014.
• [3] C. Feichtenhofer, A. Pinz, and A. Zisserman, “Convolutional Two-Stream Network Fusion for Video Action Recognition,” 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1933-1941, IEEE, June 2016. 10.1109/cvpr.2016.213
• [4] L. Wang, Y. Xiong, Z. Wang, Y. Qiao, D. Lin, X. Tang, and L. van Gool, “Temporal segment networks: Towards good practices for deep action recognition,” European Conference on Computer Vision ECCV 2016, vol.9912, pp.20-36, Springer, Cham, 2016. 10.1007/978-3-319-46484-8_2
• [5] H. Wang, A. Klaser, C. Schmid, and C.-L. Liu, “Action recognition by dense trajectories,” Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR '11, Washington, DC, USA, pp.3169-3176, IEEE Computer Society, 2011. 10.1109/cvpr.2011.5995407

Terms in the title (2)： 動作認識 ,  軌道