A Method of Face Detection with Deep Models for Patrol Videos

Common face detection methods may fail in videos captured by patrol cars for the low resolution and uncooperative situation. We proposed a method to handle this problem with a parts-based deep model. Different parts of human bodies are detected for improving the accuracy of face detection in this method. A deep neural network is used for combining the detections of different parts. Experiments were conducted on two different datasets. The results demonstrate that the proposed method outperforms existing common face detection methods.