A highly efficient system for automatic face region detection in MPEG video

Human faces provide a useful cue in indexing video content. In this paper, we present a highly efficient system that can rapidly detect human face regions in MPEG video sequences. The underlying algorithm takes the inverse quantized discrete cosine transform (DCT) coefficients of MPEG video as the input, and outputs the locations of the detected face regions. The algorithm consists of three stages, where chrominance, shape, and frequency information are used, respectively. By detecting faces directly in the compressed domain, there is no need to carry out the inverse DCT transform, so that the algorithm can run faster than the real time. In our experiments, the algorithm detected 85–92% of the faces in three test sets, including both intraframe and interframe coded image frames from news video. The average run time ranges from 13–33 ms per frame. The algorithm can be applied to JPEG unconstrained images or motion JPEG video as well.