DocumentCode
3309555
Title
Extended Histogram of Gradients feature for human detection
Author
Satpathy, Amit ; Jiang, Xudong ; Eng, How-Lung
Author_Institution
Sch. of EEE, Nanyang Technol. Univ., Singapore, Singapore
fYear
2010
fDate
26-29 Sept. 2010
Firstpage
3473
Lastpage
3476
Abstract
Unsigned Histogram of Gradients (UHoG) is a popular feature used for human detection. Despite its superior performance as reported in recent literature, an inherent limitation of UHoG is that gradients of opposite directions in a cell are mapped into the same histogram bin. This is undesirable as it will produce the same UHoG feature for two different patterns. To address this problem, we propose a new feature named the Extended Histogram of Gradients (ExHoG) in this paper. It comprises two components: UHoG and a histogram of absolute bin value differences of opposite gradient directions computed from Histogram of Gradients (HoG). Our experimental results show that the proposed ExHoG consistently outperforms the standard HoG and UHoG for human detection.
Keywords
feature extraction; image recognition; extended gradient histogram; histogram bin; human detection; unsigned histogram; Feature extraction; Histograms; Humans; Image edge detection; Pixel; Support vector machines; Training; Feature Extraction; Histogram of Gradients; HoG; Human Detection; Recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location
Hong Kong
ISSN
1522-4880
Print_ISBN
978-1-4244-7992-4
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2010.5650070
Filename
5650070
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