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
Link To Document :
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