Spiral search based fast rotation estimation for efficient HEVC compression of navigation video sequences
Springer D, Frank M, Simmet F, Niederkorn D, Kaup A (2013)
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2013
Publisher: IEEE Computer Society
Pages Range: 201-204
Article Number: 6737718
Event location: San Jose, CA
ISBN: 9781479902941
Abstract
During the development and testing of navigation systems for modern cars, the video streams of the systems-under-test are carefully observed for errors of any kind. While this observation is typically carried out manually by software engineers monitoring the video output, the complexity and variety of the latest navigation systems demand an automated analysis of system functionality. Recently published work on automated error detection for navigation systems [1] can only enfold its full functionality if video sequences can be recorded and compressed in real-time, so that the full test program can be run under lab conditions after recording. However, the rotational motion of these sequences makes efficient compression a difficult task. In this paper, we present a fast and efficient method for rotation estimation, so that rotational motion compensation and thus efficient encoding can take place. Compared to existing state of the art approaches for SIFT- or SURF-based global motion estimation, our scheme requires 1/16th of the original processing time while providing almost identical quality gains of up to 2.5dB. © 2013 IEEE.
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How to cite
APA:
Springer, D., Frank, M., Simmet, F., Niederkorn, D., & Kaup, A. (2013). Spiral search based fast rotation estimation for efficient HEVC compression of navigation video sequences. In Proceedings of the 2013 Picture Coding Symposium, PCS 2013 (pp. 201-204). San Jose, CA, US: IEEE Computer Society.
MLA:
Springer, Dominic, et al. "Spiral search based fast rotation estimation for efficient HEVC compression of navigation video sequences." Proceedings of the 2013 Picture Coding Symposium, PCS 2013, San Jose, CA IEEE Computer Society, 2013. 201-204.
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