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Dense disparity map-based pedestrian detection for intelligent vehicle

Title
Dense disparity map-based pedestrian detection for intelligent vehicle
Authors
Lee, Chung-HeeKim, Dongyoung
DGIST Authors
Lee, Chung-Hee; Kim, Dongyoung
Issue Date
2016
Citation
2016 IEEE International Conference on Intelligent Transportation Engineering, ICITE 2016, 108-111
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
Abstract
In this paper, we propose the dense disparity map-based pedestrian detection method for intelligent vehicle. The dense disparity map is utilized to improve the pedestrian detection performance. Our method consists of several steps namely, obstacle area detection using road feature information and column detection, pedestrian area detection using dense disparity map-based segmentation, and pedestrian detection using optimal feature. The first step is to detect all obstacle areas using column detection and pedestrian height information. However, there are many objects in single obstacle area. Thus each obstacle area needs to be separated into single object for improving pedestrian detection performance. Thus, the second step is performed to segment the detected obstacle area. The last step is to detect only pedestrian using classifier trained by optimal feature. The optimal feature is extracted by positive and negative training images. ETH database is utilized to evaluate our proposed pedestrian detection method. © 2016 IEEE.
URI
http://hdl.handle.net/20.500.11750/3638
DOI
10.1109/ICITE.2016.7581317
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
Files:
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Collection:
Intelligent Devices and Systems Research Group2. Conference Papers


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