Extended Histogram of Gradients feature for human detection

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.

[1]  Navneet Dalal,et al.  Finding People in Images and Videos , 2006 .

[2]  Paul A. Viola,et al.  Detecting Pedestrians Using Patterns of Motion and Appearance , 2005, International Journal of Computer Vision.

[3]  Fatih Murat Porikli,et al.  Pedestrian Detection via Classification on Riemannian Manifolds , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Cordelia Schmid,et al.  Human Detection Based on a Probabilistic Assembly of Robust Part Detectors , 2004, ECCV.

[5]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[6]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[7]  Tomaso A. Poggio,et al.  A Trainable System for Object Detection , 2000, International Journal of Computer Vision.

[8]  Mei-Chen Yeh,et al.  Fast Human Detection Using a Cascade of Histograms of Oriented Gradients , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[9]  Tomaso A. Poggio,et al.  Example-Based Object Detection in Images by Components , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Ramakant Nevatia,et al.  Detection and Tracking of Multiple, Partially Occluded Humans by Bayesian Combination of Edgelet based Part Detectors , 2007, International Journal of Computer Vision.