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Journal Publication

Real-time distributed video coding for 1K-pixel visual sensor networks

This publication appears in: Journal of Electronic Imaging

Authors: J. Hanca, N. Deligiannis and A. Munteanu

Volume: 25

Issue: 4

Number of Pages: 14

Publication Date: May. 2016


Abstract:

Many applications in visual sensor networks (VSNs) demand the low-cost wireless transmission of video data. In this context, distributed video coding (DVC) has proven its potential to achieve state-of-the-art compression performance while maintaining low computational complexity of the encoder. Despite their proven capabilities, current DVC solutions overlook hardware constraints, and this renders them unsuitable for practical implementations. This paper introduces a DVC architecture that offers highly efficient wireless communication in real-world VSNs. The design takes into account the severe computational and memory constraints imposed by practical implementations on low-resolution visual sensors. We study performance-complexity trade-offs for feedback-channel removal, propose learning-based techniques for rate allocation, and investigate various simplifications of side information generation yielding real-time decoding. The proposed system is evaluated against H.264/AVC intra, Motion-JPEG, and our previously designed DVC prototype for low-resolution visual sensors. Extensive experimental results on various data show significant improvements in multiple configurations. The proposed encoder achieves real-time performance on a 1k-pixel visual sensor mote. Real-time decoding is performed on a Raspberry Pi single-board computer or a low-end notebook PC. To the best of our knowledge, the proposed codec is the first practical DVC deployment on low-resolution VSNs.

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Current ETRO Authors

Mr. Jan Hanca

+32 (0)02 629 169

jhanca@etrovub.be

more info

Prof. Dr. Ir. Nikolaos Deligiannis

+32 (0)02 629 168

ndeligia@etrovub.be

more info

Prof. Dr. Ir. Adrian Munteanu

+32 (0)02 629 168

acmuntea@etrovub.be

more info

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