Improved Shape Context algorithm for online fast recognition -an application in pedestrian detection from a moving vehicle

Min Wang, Jianqing Wang, Hong Qiao, Xianbin Cao
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引用次数: 1

Abstract

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.
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改进的形状上下文在线快速识别算法——在移动车辆行人检测中的应用
形状上下文算法是近年来提出的一种很好的物体识别方法。它在小的几何畸变和遮挡下具有鲁棒性,在缩放、平移和光照变化下具有不变性。但由于计算量大,该算法不适合在线识别。本文提出了一种改进的形状上下文算法,该算法引入了最优层次结构,并给出了新的参考点选择准则。与原形状上下文算法相比,改进算法在保持识别精度的同时大大降低了计算量。良好的实验结果表明,该算法可以应用于行人在线检测系统,这是智能交通领域的一个重要研究课题。
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