title: Integral Histogram with Random Projection for Pedestrian Detection.
abstract: In this paper, we give a systematic study to report several deep insights into the HOG, one of the most widely used features in the modern computer vision and image processing applications. We first show that, its magnitudes of gradient can be randomly projected with random matrix. To handle over-fitting, an integral histogram based on the differences of randomly selected blocks is proposed. The experiments show that both the random projection and integral histogram outperform the HOG feature obviously. Finally, the two ideas are combined into a new descriptor termed IHRP, which outperforms the HOG feature with less dimensions and higher speed.
authors.affiliation: Department of Medical Imaging, The 174th Hospital of Chnese PLA, The Succeed Hospital affiliated to Xiamen University, Xiamen, Fujian Province, China.
authors.forename: Chang-Hua
authors.initials: CH
authors.lastname: Liu
authors.affiliation: Department of Medical Imaging, The 174th Hospital of Chnese PLA, The Succeed Hospital affiliated to Xiamen University, Xiamen, Fujian Province, China.
authors.forename: Jian-Kun
authors.initials: JK
authors.lastname: Lin
mesh_terms: D000465:Algorithms; D006801:Humans; D000069636:Pedestrians