Human face detection with neural networks and the DIRECT algorithm

Based on Rowley's approach [2], this paper aims at proposing a new architecture that uses a specific optimization technique, the DIRECT (DIviding RECTangle) algorithm, to improve the efficiency of face detection in images. The system consists of two main parts: a neural network-based face detection arbitrator and a search strategy based on an integer-handling DIRECT algorithm. By the architecture, the number of arbitration is dramatically reduced, and human faces, if they are present in an image, are not restricted to predetermined resolutions and aspect ratios. Experimental results show that the proposed architecture is efficient in terms of both speed and robustness.