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Introduction
Introduction
Robust estimation of stereo disparity in bad weather
- Existing stereo matching algorithms have difficulty to calculating disparity in various environment
- Developed robust matching algorithm using geometrical features about surface of road and dynamic modeling
Development of stereo matching algorithm
- Accuracy : 95.28%
- Dense Registration : 100%
Development of stereo matching algorithm in bad weather
- 2.9sec(12 it) ※ Baseline : 12cm, CPU Intel i7-based
Contents of Research
Contents of Research
Development of robust and dense stereo matching method
Vertical-Horizontal Stixel aggregation
- Obstacle detection on the ground using disparity => separating ground, obstacle, background => removal information of ground and background
- Vertical stixel(connecting disparity label with same-value) occurs, when specific object exists
- Vertical stixel(horizontal disparity label with same-value) appears on the ground part
- Reducing error with stixel correction using relaxation labeling
Superior our algorithms
- Offer various context recognition service from captured real-time depth information around vehicle
- Dynamic obstacle detection from depth image
- Detect safety region from experimental result
Experimental Results
Experimental Results
Publication
Publication
- Kwang Hee Won, Soon Ki Jung, Billboard sweep stereo for obstacle detection in road scenes, Electronics Letters, Vol.48, No.24, pp.1528-1530, ISSN.00135194, 2012 (2012.11.22)
- Kwang Hee Won, Soon Ki Jung, hSGM: Hierarchical Pyramid Based Stereo Matching Algorithm, Lecture Notes in Computer Science, Vol.6915, pp.693-701, ISSN.03029743, 2011 (2011.08.22)
- Kwang Hee Won, Jongwoo Son, Soon Ki Jung, Stixels Estimation through Stereo Matching of Road Scenes, International Conference on Research in Adaptive and Convergent System (ACM RACS 2014), pp.116-120, 2014 (2014.10.05 ~ 2014.10.08)
- 정근호, 박정필, 원광희, 정순기, 스틱셀을 활용한 강인한 시차맵 추정, 한국 컴퓨터 그래픽스 학회 2015 학술대회, pp.53-54, 2015 (2015.07.13 ~ 2015.07.16)
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