Face detection directly from h.264 compressed video with convolutional neural network

Human faces provide a useful cue in indexing video content. In this paper, we propose a novel face detection algorithm based on a convolutional neural network architecture that can rapidly detect human face regions in video sequences encoded by H.264/AVC. By detecting faces directly in the compressed domain, we use the discrete cosine transform (DCT) coefficients in H.264 intra coding as the feature vector for face detection, thus it is not necessary to carry out additional DCT transform during the encoding or decoding process. With the face detector inside the video encoding process, we can adjust the coding parameters adaptively and allocate more resources to the macroblocks corresponding to the face regions. Some experimental results of applying the face detector on the H.264 intra coded images are given to demonstrate the performance of the proposed algorithm.