Motion vector analysis based homography estimation for efficient HEVC compression of 2D and 3D navigation video sequences

Conference contribution
(Conference Contribution)


Publication Details

Author(s): Springer D, Simmet F, Niederkorn D, Kaup A
Publication year: 2013
Pages range: 1742-1746
ISBN: 9781479923410
ISSN: 2381-8549
Language: English


Abstract


Navigation systems have become complex devices in automobiles nowadays. As part of large in-car infotainment systems, these devices undergo extensive hardware and software tests in order to assert correct system behavior under all circumstances. During field tests, the display output is typically recorded in compressed form for days or weeks, followed by a thorough analysis of the video data. In this paper, we demonstrate how to setup an HEVC-based compression solution specifically designed for navigation sequence content. We show how rotational motion, which is a dominant characteristic, can be estimated and compensated in an efficient way. We avoid any complex feature-based approaches for global motion estimation but find precise motion parameters by analyzing and filtering motion vector sets produced by HEVC during encoding. While achieving compression efficiency similar to a feature-based approach, processing time for global motion estimation can be significantly reduced. © 2013 IEEE.


FAU Authors / FAU Editors

Kaup, André Prof. Dr.-Ing.
Lehrstuhl für Multimediakommunikation und Signalverarbeitung
Springer, Dominic
Lehrstuhl für Multimediakommunikation und Signalverarbeitung


How to cite

APA:
Springer, D., Simmet, F., Niederkorn, D., & Kaup, A. (2013). Motion vector analysis based homography estimation for efficient HEVC compression of 2D and 3D navigation video sequences. In Proceedings of the 2013 20th IEEE International Conference on Image Processing, ICIP 2013 (pp. 1742-1746). Melbourne, VIC, AU.

MLA:
Springer, Dominic, et al. "Motion vector analysis based homography estimation for efficient HEVC compression of 2D and 3D navigation video sequences." Proceedings of the 2013 20th IEEE International Conference on Image Processing, ICIP 2013, Melbourne, VIC 2013. 1742-1746.

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Last updated on 2019-25-04 at 17:23