Pedestrian Detection using Fuzzy Clustering and Histogram of Oriented Gradients

被引:1
作者
Malireddi, Harshitha [1 ]
Rajitha, B. [1 ]
Parwani, Kiran [1 ]
机构
[1] Natl Inst Technol, Comp Sci & Engn, Allahabad, Uttar Pradesh, India
来源
2019 5TH IEEE INTERNATIONAL WIE CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (WIECON-ECE 2019) | 2019年
关键词
Histogram of Gradients; Background; Fuzzy clustering; Contour Detection; Cluster centres;
D O I
10.1109/wiecon-ece48653.2019.9019930
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Pedestrian detection with complex scenes from a video is an challenging task due to illumination variations and dynamic background changes. In this context, this paper proposes a efficient approach of using fuzzy clustering and Histogram of Gradients for detecting humans. For this task, the paper first initializes a background frame where only static objects are present using fuzzy c-means clustering. Then a background subtraction and foreground detection algorithm (binary threshold) is proposed for detecting the moving objects. A contour is fetched for these foreground objects and passed through HOG classifier for pedestrian detection. The proposed method has been tested on various complex scenes from different data-sets.And it has presented better results over literature methods in terms of classification accuracy of 92%.
引用
收藏
页数:4
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