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Proceedings Paper

Variational optical flow estimation for images with spectral and photometric sensor diversity
Author(s): Tomas Bengtsson; Tomas McKelvey; Konstantin Lindström
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Paper Abstract

Motion estimation of objects in image sequences is an essential computer vision task. To this end, optical flow methods compute pixel-level motion, with the purpose of providing low-level input to higher-level algorithms and applications. Robust flow estimation is crucial for the success of applications, which in turn depends on the quality of the captured image data. This work explores the use of sensor diversity in the image data within a framework for variational optical flow. In particular, a custom image sensor setup intended for vehicle applications is tested. Experimental results demonstrate the improved flow estimation performance when IR sensitivity or flash illumination is added to the system.

Paper Details

Date Published: 4 March 2015
PDF: 7 pages
Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431U (4 March 2015); doi: 10.1117/12.2180109
Show Author Affiliations
Tomas Bengtsson, Chalmers Univ. of Technology (Sweden)
Tomas McKelvey, Chalmers Univ. of Technology (Sweden)
Konstantin Lindström, Volvo Cars AB (Sweden)

Published in SPIE Proceedings Vol. 9443:
Sixth International Conference on Graphic and Image Processing (ICGIP 2014)
Yulin Wang; Xudong Jiang; David Zhang, Editor(s)

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