A Psychological Adaptive Model For Video Analysis

Extracting key-frames is the first step for efficient content-based indexing, browsing and retrieval of the video data in commercial movies. Most of the existing research deals with “how to extract representative frames? ” However the unaddressed question is “how many key-frames are required to represent a video shot properly? ” Generally, the user defines this number a priori or some heuristic methods are used. In this paper, we propose a psychological model, which computes this number adaptively and online, from variation of visual features in a video-shot. We incorporate it with an iterative key-frame selection method to automatically select the key-frames. We compare the results of this method with two other well-known approaches, based on a novel effectiveness measure that scores each approach based on its representational power. Movie-clips of varying complexity are used to underscore the success of the proposed model in real-time. 1