Localizing volumetric motion for action recognition in realistic videos

• Main Authors: WU, Xiao, NGO, Chong-wah, LI, Jintao, ZHANG, Yongdong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2009
• Subjects: Human action recognition; Keypoint trajectory; Mean-shift clustering; Motion subspace learning; Realistic videos; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6370; https://ink.library.smu.edu.sg/context/sis_research/article/7373/viewcontent/10.1.1.567.4273.pdf
• Institution: Singapore Management University

This paper presents a novel motion localization approach for recognizing actions and events in real videos. Examples include StandUp and Kiss in Hollywood movies. The challenge can be attributed to the large visual and motion variations imposed by realistic action poses. Previous works mainly focus...