Real-time face detection using hybrid GA based on selective attention

There have been many attempts to realize human-like visual function by image processing. Methods for recognition and tracking of the human face are expected to be applied in security systems and in the field of ITS (intelligent transport systems). This study was performed to construct a detection system capable of recognizing multiple areas of the human face in real tune. We employed a hybrid GA (genetic algorithm) based on selective attention, which is the human visual function used to reduce processing load, to search for the position of a face in input images. The hybrid GA consisted of random searching as a rough search and an improved GA that performed a more careful search. These methods were combined by grouping to allow simultaneous detection of multiple faces in input images in real time. We confirmed the effectiveness of our proposed detection system by experiments involving detection of multiple targets.