Automated Activity Detection as a Pre - processing stage of Video Camera feeds

In this paper, we describe a simple but effective and fast video activity detection algorithm to provide an efficient pre-processing tool for video camera feeds. It also presents a range of applications, including post production of TV camera video streams, analysis of surveillance videos, visual scene classification, and camera control for automated recordings etc. Given a video sequence, our algorithm detects moving pixels by modeling their differences in Gaussian distribution through on-line estimation of their statistics to determine an adaptive threshold for final classification of active or static scenes. The originality of our contribution can be highlighted as: (i) a powerful activity detection tool inside videos to facilitate efficient visual content analysis; (ii) on-line estimation of statistics and adaptive determination of a threshold for automated classification of active or static scenes. Extensive testing supports that the proposed algorithm achieves excellent performances. Indexing terms: automated video activity detection, video processing