Incremetal Spatio-Temporal Feature Extraction and Retrieval for Large Video Database

In this paper we present a novel framework for semantic retrieval of video database. Each frame of video clips, characterized by its HSV (hue-saturation-value) color feature, is first projected onto the spatial principle components via CCIPCA (candid covariance-free incremental principal component analysis). Temporal Chebyshev polynomials for video clips of various lengths are captured subsequently. The similarity of two video clips is finally presented in a reasonable and computable form. The framework works incrementally and is suitable for videos of data streams in sequential order. Extensive experiments demonstrate that the framework can obtain promising results on video similarity comparison, and also with a comparably computational speedup.