Action recognition in video is an important part of many applications. While the performance of action recognition has been intensively investigated, not much research so far has been done in understanding of how long sequence of video frames is needed to correctly recognize certain actions. This paper presents a new method of measurement of the necessary length of the video sequence needed to recognize the actions based on space-time feature points - the critical information necessary to successfully recognize the actions in real-time. The proposed methods is experimentally evaluated on human action recognition dataset.
['Ivo Reznícek', 'Pavel Zemcik']
Human Action Recognition for Real-time Applications