Name
Abstract | ||
|---|---|---|
In this paper, we consider the problem of distributed compres- sion in camera sensor networks. Due to the spatial proximity of the different cameras, acquired images can be highly dependent. The correlation in the visual information retrieved is related to the structure of the plenoptic function and can be estimated using geo- metrical information such as the position of the cameras and some bounds on the location of the objects. We propose a distributed compression scheme that takes ad- vantage of this geometrical information in order to reduce the over- all transmission rate from the sensors to a common central receiver. This new approach allows for a flexible repartition of the transmis- sion bit-rates amongst the encoders and is optimal in many cases. Moreover, we show that our coding scheme can be made resilient to a fixed number of occlusions and that perfect reconstruction and interpolation are possible at the receiver. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/ICIP.2004.1418807 | Image Processing, 2004. ICIP '04. 2004 International Conference |
Keywords | Field | DocType |
image coding,image reconstruction,interpolation,source coding,camera sensor networks,coding,common central receiver,distributed compression,geometrical information,interpolation,occlusions,perfect reconstruction,plenoptic function,transmission bit-rate repartitioning | Iterative reconstruction,Transmission rate,Compression (physics),Computer vision,Source code,Computer science,Interpolation,Coding (social sciences),Camera sensor networks,Artificial intelligence,Encoder | Conference |
Volume | ISSN | ISBN |
1 | 1522-4880 | 0-7803-8554-3 |
Citations | PageRank | References |
9 | 0.75 | 9 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Gehrig | 1 | 65 | 5.40 |
| Dragotti, P.L. | 2 | 512 | 39.29 |