Title :
Robust motion detection using histogram of oriented gradients for illumination variations
Author :
Hu, Lei ; Liu, Weibin ; Li, Bo ; Xing, Weiwei
Author_Institution :
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., Beijing, China
Abstract :
This paper proposes a robust motion detection method for illumination variations which uses histogram of oriented gradients. The detection process is divided into two phases: coarse detection and refinement. In the coarse detection phase, first, a texture-based background model is built which implements a group of adaptive histograms of oriented gradients; then, by comparing the histogram of oriented gradients of each pixel between current frame and background model, a foreground is segmented based on texture feature which is not susceptible to illumination variations, whereas some missing foreground regions exist; finally, the result based on texture is optimized by combining the pixel-wise detection result produced by Gaussian Mixture Model (GMM) algorithm, which greatly improves the detection performance by incorporating efficient morphological operations. In the refinement phase, the above detection result is refined based on the distinction in color feature to eliminate errors like shadows, noises, redundant contour, etc. Experimental results show the effectiveness and robustness of our approach in detecting moving objects in varying illumination conditions.
Keywords :
Bayesian methods; Colored noise; Gaussian distribution; Histograms; Layout; Lighting; Motion detection; Object detection; Phase detection; Robustness; foreground segmentation; histogram of oriented gradients; illumination variations; motion detection;
Conference_Titel :
Industrial Mechatronics and Automation (ICIMA), 2010 2nd International Conference on
Conference_Location :
Wuhan, China
Print_ISBN :
978-1-4244-7653-4
DOI :
10.1109/ICINDMA.2010.5538276