Introduction to the theory of neural computation
Introduction to the theory of neural computation
Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
On face detection in the compressed domain
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Robust Real-Time Face Detection
International Journal of Computer Vision
Convolutional Face Finder: A Neural Architecture for Fast and Robust Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A highly efficient system for automatic face region detection in MPEG video
IEEE Transactions on Circuits and Systems for Video Technology
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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.