Fast Human Detection Based on Parallelogram Haar-Like Features

Inspired by a recent image descriptors for object detection, this paper proposed the feature description method based on set of modified Haar-Iike features which have parallelogram shapes. Using the proposed feature descriptors to develop a rapid detection system for human detection based on cascade structure used for boosting classifier. Specially, human detection in omnidirectional image as well as unwrap omnidirectional to panoramic image were described in this paper. The experimental results showed that the proposed method could produce high accuracy detection rate with lower false positive rate and higher recall rate than Haar-like features, and faster than HOG feature. It is efficiency with different resolutions and poses under a variety conditional such as flare illumination, clutter backgrounds, and so on.