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http://dx.doi.org/10.5370/KIEEP.2016.65.1.066

Pedestrian Detection using RGB-D Information and Distance Transform  

Lee, Ho-Hun (School of Electronics Engineering, Chungbuk National University)
Lee, Dae-Jong (School of Electronics Engineering, Chungbuk National University)
Chun, Myung-Geun (School of Electronics Engineering, Chungbuk National University)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.65, no.1, 2016 , pp. 66-71 More about this Journal
Abstract
According to the development of depth sensing devices and depth estimation technology, depth information becomes more important for object detection in computer vision. In terms of recognition rate, pedestrian detection methods have been improved more accurately. However, the methods makes slower detection time. So, many researches have overcome this problem by using GPU. Here, we propose a real-time pedestrian detection algorithm that does not rely on GPU. First, the depth-weighted distance map is used for detecting expected human regions. Next, human detection is performed on the regions. The performance for the proposed approach is evaluated and compared with the previous methods. We show that proposed method can detect human about 7 times faster than conventional ones.
Keywords
Pedestrian detection; RGB-D; Distance transform;
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Times Cited By KSCI : 2  (Citation Analysis)
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