Video categorization using object of interest detection

Object of Interest (OOI) detection has been widely used in many recent works in video analysis, especially in video similarity and video retrieval. In this paper, we describe a generic video classification algorithm using object of interest detection. We use online user-submitted videos and aim to categorize the videos into six broad categories hot star, news, anime, pets, sports and commercials. We show through our experiments that, detecting and describing the object of interest improves the video classification accuracy by about 10 percentage points.