Detecting and recognizing human action in videos - Yu, Gang (2014)
Detecting and recognizing human actions is of great importance to video analytics due to its numerous applications in video surveillance and human computer interaction. Despite much previous work, fast and reliable action detection and recognition in unconstrained videos remain a challenging problem. First of all, actions are spatio-temporal patterns characterized by both motion and appearance features. The same type of action may exhibit large variations due to the changes of motion speed, scale, view point, clothing, not to mention partial occlusions. It is thus a challenge to perform robust action matching that is insensitive to such variations, especially if only a limited number of training examples are provided. Moreover, fast action detection and localization is another challenging issue in cluttered and dynamic environment. Compared with image based object detection which only requires spatial localization, action localization is in spatio-temporal video space thus is much more time consuming.