8 March 2018 HOG pedestrian detection based on edge symmetry and trilinear interpolation
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Proceedings Volume 10609, MIPPR 2017: Pattern Recognition and Computer Vision; 1060907 (2018) https://doi.org/10.1117/12.2282815
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
In computer vision, pedestrian detection is a key problem. In this paper, we propose to speed up the HOG+SVM algorithm without sacrificing the classification accuracy. In order to eliminate the effects of aliasing phenomenon that products in the process of HOG extraction, we used trilinear interpolation to extract feature. This paper proposed HOG pedestrian detection method based on edge symmetry. In these experiments, we used INRIA dataset. Traditional HOG pedestrian detection is presence of slow detection speed and low detection rate. Experiments show that using trilinear interpolation and edge symmetry not only can improve the detection effect, but also can improve the detection rate.
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Dandan Wang, Dandan Wang, Tongei Lu, Tongei Lu, Yanduo Zhang, Yanduo Zhang, } "HOG pedestrian detection based on edge symmetry and trilinear interpolation", Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 1060907 (8 March 2018); doi: 10.1117/12.2282815; https://doi.org/10.1117/12.2282815
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