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Pedestrian detection using hog-based block selection

Title
Pedestrian detection using hog-based block selection
Authors
Kang, MinsungLim, Young Chul
DGIST Authors
Kang, Minsung; Lim, Young Chul
Issue Date
2014
Citation
11th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014, 2, 783-787
Type
Conference
Article Type
Conference Paper
ISBN
9789897580406
Abstract
Recently, pedestrian detection methods have been popularly used in the field of intelligent vehicles. In most previous works, the Histogram of Oriented Gradients (HOG) is used to extract features for pedestrian detection. However HOG is difficult to use in the real-time operating system of an intelligent vehicle. In this paper, we proposed a pedestrian detection method using a HOG-based block selection. First, we analyse the HOG block and select the parts of the block with a high hit rate. We then use only 20% of the total HOG blocks for the pedestrian feature. The proposed method is 5 times faster than methods using the entire feature, while performance remains almost the same.
URI
http://hdl.handle.net/20.500.11750/3792
Publisher
SciTePress
Files:
There are no files associated with this item.
Collection:
Convergence Research Center for Future Automotive Technology2. Conference Papers


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