NDLI: A new Local-Main-Gradient-Orientation HOG and contour differences based algorithm for object classification

Content Provider	IEEE Xplore Digital Library
Author	Xiaoqiong Su Weiyao Lin Xiaozhen Zheng Xintong Han Hang Chu Xiaoyun Zhang
Copyright Year	2013
Description	Author affiliation: Res. Dept. of Hisilicon Semicond. & Component Bus. Dept., Huawei Technol., China (Xiaozhen Zheng) \|\| Dept. of Electron. Eng., Shanghai Jiao Tong Univ., Shanghai, China (Xiaoqiong Su; Weiyao Lin; Xintong Han; Hang Chu; Xiaoyun Zhang)
Abstract	This paper presents a new algorithm to better classify objects in videos. In our case, the objects are cars, vans, and people on the roads. First, in order to extract the moving objects more precisely, we have proposed a method for foreground extraction based on the contour differences between the video frame and the background image. Second, after we got the integrated moving object, we have proposed a new algorithm to extract better features from the object. The new algorithm is based on two extended Histogram of Oriented Gradient (HOG) descriptor. We have improved HOG in two aspects: (a) selecting the gradient information from the moving objects and discarding the background gradient; (b) weighting every bin of gradient orientation histogram according to their significance within predefined area, in order to emphasize the important gradient information. We obtained Contour-Difference HOG (CD-HOG) from the first extension and Local-Main-Gradient-Orientation HOG (LMGO-HOG) from the second extended HOG. These extensions can cope with the cluttered background and make the features more distinguishable. Each of the extended HOG descriptors can produce a satisfying performance separately and an even better one if they are applied in cascade. From extensive evaluations, we showed the wonderful performance of our algorithm, and the accuracy rate of 94.04% can be achieved in some cases.
Starting Page	2892
Ending Page	2895
File Size	1055299
Page Count	4
File Format	PDF
ISBN	9781467357609
ISSN	02714302
e-ISBN	9781467357623
DOI	10.1109/ISCAS.2013.6572483
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Videos Feature extraction Classification algorithms Histograms Noise Pattern recognition Lighting
Content Type	Text
Resource Type	Article

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