Improved shape context algorithm for online fast recognition - An application in pedestrian detection from a moving vehicle

Shape Context algorithm is a recently proposed good method for object recognition. It is robust under small geometrical distortions and occlusion, invariant under scaling, translation, and change of illumination. However, because of its computational complexity, this algorithm is not suitable for online recognition. In this paper, we proposed an improved Shape Context algorithm which introduces an optimal hierarchical structure and gives new reference points selection criteria. Compared with the original Shape Context algorithm, the improved algorithm keeps the recognition accuracy and reduces the computational cost greatly. The good experimental results reveal that, this new algorithm can be applied to the pedestrian detection system online, which is an important research topic in intelligent transportation.