Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 조성호 | - |
dc.date.accessioned | 2018-03-23T02:46:17Z | - |
dc.date.available | 2018-03-23T02:46:17Z | - |
dc.date.issued | 2012-12 | - |
dc.identifier.citation | International Journal of Distributed Sensor Networks , 2012, 2012, P.352167 | en_US |
dc.identifier.issn | 1550-1477 | - |
dc.identifier.uri | http://journals.sagepub.com/doi/10.1155/2012/352167 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/51106 | - |
dc.description.abstract | With the booming of video devices ranging from low-power visual sensors to mobile phones, the video sequences captured by these simple devices must be compressed easily and reconstructed by relatively more powerful servers. In such scenarios, distributed compressed video sensing (DCVS), combining distributed video coding (DVC) and compressed sensing (CS), is developed as a novel and powerful signal-sensing and compression algorithm for video signals. In DCVS, video frames can be compressed to a few measurements in a separate manner, while the interframe correlation is explored by the joint recovery algorithm. In this paper, a new DCVS joint recovery scheme using side-information-based belief propagation (SI-BP) is proposed to exploit both the intraframe and interframe correlations, which is particularly efficient over error-prone channels. The DCVS scheme using SI-BP is designed over two frame signal models, the mixture Gaussian (MG) model and the wavelet hidden Markov tree (WHMT) model. Simulation results evaluated on two video sequences illustrate that the SI-BP-based DCVS scheme is error resilient when the measurements are transmitted through the noisy wireless channels. | en_US |
dc.description.sponsorship | This work is supported by National Science Foundation of China (no. 61201149), the 111 Project (no. B08004), and the Fundamental Research Funds for the Central Universities. This work is also supported (in part) by Korea Evaluation Institute of Industrial Technology (KEIT), under the R&D support program of Ministry of Knowledge Economy, Korea. The authors would like to thank all of the reviewers and editors for their detailed comments that have certainly improved the quality of their paper. | en_US |
dc.language.iso | en | en_US |
dc.publisher | SAGE PUBLICATIONS INC | en_US |
dc.subject | UNCERTAINTY PRINCIPLES | en_US |
dc.subject | SIGNAL RECONSTRUCTION | en_US |
dc.subject | INFORMATION | en_US |
dc.subject | PROJECTION | en_US |
dc.title | Distributed Compressed Video Sensing in Camera Sensor Networks | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1155/2012/352167 | - |
dc.relation.page | 1-10 | - |
dc.relation.journal | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | - |
dc.contributor.googleauthor | Liu, Yu | - |
dc.contributor.googleauthor | Zhu, Xuqi | - |
dc.contributor.googleauthor | Zhang, Lin | - |
dc.contributor.googleauthor | Cho, SungHo | - |
dc.relation.code | 2012214709 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | DEPARTMENT OF ELECTRONIC ENGINEERING | - |
dc.identifier.pid | dragon | - |
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