文章基本信息

标题：Crowded Pedestrian Detection and Density Estimation by Visual Words Analysis
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作者：Shilin Zhang ; Xunyuan Zhang
期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2015
卷号：10
期号：3
页码：99-108
DOI：10.14257/ijmue.2015.10.3.10
出版社：SERSC
摘要：Crowded pedestrian detection and density estimation are very useful and important under transportation environment. In this paper, we present a novel method for crowded pedestrian detection and density estimation through a weighting scheme of bag of visual words model which characterizes both the weight and the relative spatial arrangement aspects of visual words in depicting an image. Firstly, we analyze the visual words generation process. We give each visual word a weight by counting the number of images through which each visual word is clustered and computing the cluster radius of each visual word. To be more specifically, the co-occurrences of visual words are computed with respect to spatial predicates over a hierarchical spatial partitioning of an image. We validate this method using a challenging ground truth pedestrian dataset Pascal VOC 2007. Our approach is shown to be more accuracy than a non-weighting bag-of-visual- words one. The algorithm's cost is also more efficient than the competing pairs.
关键词：crowded pedestrian detection; pedestrian density estimation; automotive ; safety