Content-based search of video using color, texture, and motion

We present an implementation of a system for content-based search and retrieval of video based on low-level visual features. Currently the system consists of three parts, automatic video partition, feature extraction, video search and retrieval. Three primary features, color texture and motion are used for indexing. They are represented by color histogram, Gabor texture features, and motion histogram. Most of the processing is done directly in the MPEG compressed domain. Testing on sports and movie databases have shown good retrieval performance.