New approach for moving point detection: Application to video space-time description

Local space time points detection and description have recently emerged as a major research in based video analysis content in video surveillance and event detection applications. Several works extend tow dimensional descriptor to the temporal dimension. Most of the existing methods consider the video as a spatio-temporal volume and then describe the volumetric region around the salient point in 3D. However, this representation requires a high operational complexity. In this works we propose a new approach to describe motion using a simple 2D representation of the video. Our method is based on tracked feature points in image sequence. The main challenge in motion description is how to detect the local motion information. In this paper we aim to describe motion around moving point without the need to extend them on the 3D dimension. To show the efficiency and accuracy of our approach, we perform action recognition experiments on the KTH and Weizmann databases using the bag of words approach. We have obtained impressive results for action recognition.