NDLI: Real-time vehicle back-up warning system with a single camera

Content Provider	IEEE Xplore Digital Library
Author	Jun Cao Yilin Wang Baoxin Li
Copyright Year	2015
Description	Author affiliation: Intel Corp., Chandler, AZ, USA (Jun Cao) \|\| Arizona State Univ., Chandler, AZ, USA (Yilin Wang; Baoxin Li)
Abstract	In this paper, we propose a real-time system using vehicle back-up camera to alert for potential back-up collisions. We developed a highly efficient algorithm, combining segmenting pedestrians and vehicles from moving background using local optical flow value, and a scale adaptive method using Deformable Part Model to detect objects at different distances. To test out algorithm, we created our own vehicle back-up dataset that contains rich scenes recorded from a back-up camera on moving/stationary vehicles with unique and challenging scenarios such as frequent occlusion with cluttered and moving background, and we made this dataset available to public for other researchers. Experiments on the dataset shows that our algorithm achieves high accuracy in near real-time, and it is about 10 times faster than the comparable state-of-the-art algorithm.
Starting Page	2275
Ending Page	2279
File Size	4265566
Page Count	5
File Format	PDF
e-ISBN	9781479983391
DOI	10.1109/ICIP.2015.7351207
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-27
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Cameras Real-time systems Measurement Deformable models Optical imaging Support vector machines Latent SVM Computer Vision Vehicle Safety Optical Flow Deformable Part Model
Content Type	Text
Resource Type	Article

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