NDLI: Color-Based Free-Space Segmentation Using Online Disparity-Supervised Learning

Content Provider	IEEE Xplore Digital Library
Author	Sanberg, W.P. Dubbelman, G. De With, P.H.N.
Copyright Year	2015
Description	Author affiliation: Dept. of Electr. Eng., Eindhoven Univ. of Technol., Eindhoven, Netherlands (Sanberg, W.P.; Dubbelman, G.; De With, P.H.N.)
Abstract	This work contributes to vision processing for Advanced Driver Assist Systems (ADAS) and intelligent vehicle applications. We propose a color-only stixel segmentation framework to segment traffic scenes into free, drivable space and obstacles, which has a reduced latency to improve the real-time processing capabilities. Our system learns color appearance models for free-space and obstacle classes in an online and self-supervised fashion. To this end, it applies a disparity-based segmentation, which can run in the background of the critical system path, either with a time delay of several frames or at a frame rate that is only a third of that of the color-based algorithm. In parallel, the most recent video frame is analyzed solely with these learned color appearance models, without an actual disparity estimate and the corresponding latency. This translates into a reduced response time from data acquisition to data analysis, which is a critical property for high-speed ADAS. Our evaluation on two publicly available datasets, one of which we introduce as part of this work, shows that the color-only analysis can achieve similar or even better results in difficult imaging conditions, compared to the disparity-only method. Our system improves the quality of the free-space analysis, while simultaneously lowering the latency and the computational load.
Starting Page	906
Ending Page	912
File Size	2417658
Page Count	7
File Format	PDF
ISSN	21530017
e-ISBN	9781467365963
DOI	10.1109/ITSC.2015.152
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-15
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image color analysis Cameras Estimation Histograms Robustness Roads Image segmentation
Content Type	Text
Resource Type	Article

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