|
|
Low-Dimensional Histogram of Oriented Gradients with Non-Overlapping Scheme |
HUO Ya-Song1,2,ZHANG Kun2 |
School of Electronic Information Engineering,Tianjin University,Tianjin 300072 College of Management and Economics,Tianjin University,Tianjin 300072 |
|
|
Abstract As a derivation version of scale-invariant feature transform (SIFT),histogram of oriented gradients (HOG) is widely used in human detection,gesture recognition,face recognition,scene classification,etc. However,the high dimension of the HOG feature vector leads to the curse of the dimensionality and high computation complexity. In this paper,it is found that the high dimension of HOG feature vector results from computing histograms of overlapping blocks. Though overlapping block is useful for enhancing the robustness,it leads to redundant information. To reduce the redundant information and the number of features as well,a non-overlapping version of HOG is proposed. The dimensions of the proposed method are 1/3 of those of traditional ones. The experimental results on palm and human detection demonstrate the efficiency and effectiveness of the proposed method.
|
Received: 13 November 2012
|
|
|
|
|
[1] Pang Y W,Yan H,Yuan Y,et al. Robust CoHOG Feature Extraction in Human-Centered Image/Video Management System. IEEE Trans on Systems,Man,and Cybernetics,2012,42(2): 458-468 [2] Lowe D G. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision,2004,60(2): 91-110 [3] Tuzel O,Porikli F,Meer P. Pedestrian Detection via Classification on Riemannian Manifolds. IEEE Trans on Pattern Analysis and Machine Intelligence,2008,30(10): 1713-1727 [4] Pang Y W,Yuan Y,Li X L. Gabor-Based Region Covariance Matrices for Face Recognition. IEEE Trans on Circuits and System for Video Technology,2008,18(7): 989-993 [5] Ahonen T,Hadid A,Pietikinen M. Face Description with Local Binary Patterns: Application to Face Recognition. IEEE Trans on Pattern Analysis and Machine Intelligence,2006,28(12): 2037-2041 [6] Calonder M,Lepetit V,O¨zuysal M,et al. BRIEF: Computing a Local Binary Descriptor Very Fast. IEEE Trans on Pattern Analysis and Machine Intelligence,2012,34(7): 1281-1298 [7] Guo Z H,Zhang L,Zhang D. A Completed Modeling of Local Binary Pattern Operator for Texture Classification. IEEE Trans on Image Processing,2010,19(6): 1657-1663 [8] Dalal N,Triggs B. Histograms of Oriented Gradients for Human Detection // Proc of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego,USA,2005,I: 886-893 [9] Pang Y W,Yuan Y,Li X L,et al. Efficient HOG Human Detection. Signal Processing,2011,91(4): 773-781 [10] Linde O,Lindeberg T. Composed Complex-Cue Histograms: An Investigation of the Information Content in Receptive Field Based Image Descriptors for Object Recognition. Computer Vision and Image Understanding,2012,116(4): 538-560 [11] Déniz O,Bueno G,Salido J,et al. Face Recognition Using Histograms of Oriented Gradients. Pattern Recognition Letters,2011,32(12): 1598-1603 [12] Chandrasekhar V,Takacs G,Chen D M,et al. Compressed Histogram of Gradients: A Low-Bitrate Descriptor. International Journal of Computer Vision,2012,96(3): 384-399 [13] Ikizler N,Duygulu P. Histogram of Oriented Rectangles: A New Pose Descriptor for Human Action Recognition. Image and Vision Computing,2009,27(10): 1515-1526 [14] Bay H,Ess A,Tuytelaars T,et al. Speeded-Up Robust Features (SURF). Computer Vision and Image Understanding,2008,110(3): 346-359 [15] Tola E,Lepetit V,Fua P. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo. IEEE Trans on Pattern Analysis and Machine Intelligence,2010,32(5): 815-830 [16] Jain A K,Duin R P W,Mao J C. Statistical Pattern Recognition: A Review. IEEE Trans on Pattern Analysis and Machine Intelligence,2000,22(1): 4-37 [17] Wang X Y,Han T X,Yan S C. An HOG-LBP Human Detector with Partial Occlusion Handling // Proc of the IEEE International Conference on Computer Vision. Kyoto,Japan,2009: 32-39 [18] Wang X N,Qiu L K,Cheng Y,et al. An Area Ratio between Rings Based Translation,Rotation and Scale Invariant Descriptor. Pattern Recognition and Artificial Intelligence,2012,25(1): 82-88 (in Chinese) (王晓年,邱立可,程 宇,等,一种基于环间面积比的旋转、平移和缩放不变性描述符.模式识别与人工智能,2012,25(1): 82-88) [19] Yin F,Jiao L C. Robust Remote Sensing Image Target Recognition Based on Extending Training Set by Rotation and Sparse Representation. Pattern Recognition and Artificial Intelligence,2012,25(1): 89-95 (in Chinese) (殷 飞,焦李成,基于旋转扩展和稀疏表示的鲁棒遥感图像目标识别.模式识别与人工智能,2012,25(1): 89-95) |
|
|
|