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Proceedings Paper

Forward rectification: spatial image normalization for a video from a forward facing vehicle camera
Author(s): Viktor Prun; Dmitri Polevoy; Vassiliy Postnikov
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Paper Abstract

The work in this paper is focused around visual ADAS (Advanced Driver Assistance Systems). We introduce forward rectification – a technique for making computer vision algorithms more robust against camera mount point and mount angles. Using the technique can increase the quality of recognition as well as lower the dimensionality for algorithm invariance, making it possible to apply simpler affine-invariant algorithms for applications that require projective invariance. Providing useful results this rectification requires thorough calibration of the camera, which can be done automatically or semi-automatically. The technique is of general nature and can be applied to different algorithms, such as pattern matching detectors, convolutional neural networks. The applicability of the technique is demonstrated on HOG-based car detector detection rate.

Paper Details

Date Published: 17 March 2017
PDF: 5 pages
Proc. SPIE 10341, Ninth International Conference on Machine Vision (ICMV 2016), 103410W (17 March 2017); doi: 10.1117/12.2268605
Show Author Affiliations
Viktor Prun, Cognitive Technologies (Russian Federation)
Dmitri Polevoy, Cognitive Technologies (Russian Federation)
Federal Research Ctr. (Russian Federation)
National Univ. of Science and Technology (Russian Federation)
Vassiliy Postnikov, Cognitive Technologies (Russian Federation)
Federal Research Ctr. (Russian Federation)


Published in SPIE Proceedings Vol. 10341:
Ninth International Conference on Machine Vision (ICMV 2016)
Antanas Verikas; Petia Radeva; Dmitry P. Nikolaev; Wei Zhang; Jianhong Zhou, Editor(s)

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