Scalable Saliency-Aware Distributed Compressive Video Sensing

Jin Xu, Soufiene Djahel, Yuansong Qiao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


Distributed compressive video sensing (DCVS) is an emerging low-complexity video coding framework which integrates the merits of distributed video coding (DVC) and compressive sensing (CS). Because the human visual system (HVS) is the ultimate receiver of visual signals, we aim to improve the perceptual rate-distortion performance of DCVS by designing a novel scalable saliency-aware DCVS codec. Firstly, we perform saliency estimation in the the side information (SI) frame generated at the decoder side and adaptively control the size of region-of-interest (ROI) according to the measurements budget by applying a saliency guided foveation model. Subsequently, based on online estimation of the correlation noise between a non-key frame and its SI, we develop a saliency-aware block compressive sensing scheme to more accurately reconstruct the ROI of each non-key frame. The obtained experimental results reveal that our DCVS codec outperforms the legacy DCVS codecs in terms of the perceptual rate-distortion performance.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Symposium on Multimedia, ISM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781509003792, 9781509003785
Publication statusPublished - 28 Mar 2016
Externally publishedYes
Event17th IEEE International Symposium on Multimedia - Miami, United States
Duration: 14 Dec 201516 Dec 2015
Conference number: 17


Conference17th IEEE International Symposium on Multimedia
Abbreviated titleISM 2015
Country/TerritoryUnited States


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