NDLI: Off-vehicle evaluation of camera-based pedestrian detection

Content Provider	IEEE Xplore Digital Library
Author	Alon, Y. Bar-Hillel, A.
Copyright Year	2012
Description	Author affiliation: RoadMetric LTD, Giveat Yearim 90970, Israel (Alon, Y.) \|\| GM Advanced Technical Center Israel, Hamada 7, Herliya, Isarel (Bar-Hillel, A.)
Abstract	Performance evaluation and comparison of vision-based automotive modules is a growing need in automotive industry. Off-vehicle evaluation, using a database of video streams offers many advantages over on-vehicle evaluation in terms of reduced costs, repeatability and the ability to compare different modules under the same conditions. An off-vehicle evaluation platform for camera based pedestrian detection is presented, enabling evaluation of industrial modules and internally developed algorithms. In order to maintain a single video database despite variability in camera location and internal parameters, experiments were done with video warping techniques, in which a video is warped to look as if taken from a target camera. To obtain ground truth annotation, both manual and Lidar-based methods were tested. Lidar-based annotation was shown to achieve detection rate > 80% without human intervention, which can go up to 97.5% using a semi-supervised methodology with moderate human effort. Finally, we examined several performance metrics, and found that the image-based detection criteria used in most of the literature does not fit certain automotive application well. A modified criterion based on real world coordinates is suggested.
Starting Page	352
Ending Page	358
File Size	1856501
Page Count	7
File Format	PDF
ISBN	9781467321198
ISSN	19310587
e-ISBN	9781467321181
DOI	10.1109/IVS.2012.6232160
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Databases Lenses Humans Laser radar Manuals Vehicles
Content Type	Text
Resource Type	Article

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