Abstract

Action Recognition in videos is an active research field that is fueled by an acute need, spanning several application domains. Still, existing systems fall short of the applications’ needs in real-world scenar- ios, where the quality of the video is less than optimal and the viewpoint is uncontrolled and often not static. In this paper, we consider the key elements of motion encoding and focus on capturing local changes in mo- tion directions. In addition, we decouple image edges from motion edges using a suppression mechanism, and compensate for global camera mo- tion by using an especially fitted registration scheme. Combined with a standard bag-of-words technique, our methods achieves state-of-the-art performance in the most recent and challenging benchmarks.