| Paper: | WA-L5.1 |
| Session: | Video Surveillance II |
| Time: | Wednesday, September 19, 09:50 - 10:10 |
| Presentation: |
Lecture
|
| Title: |
LIFETIME-DISTORTION TRADE-OFF IN IMAGE SENSOR NETWORKS |
| Authors: |
Chao Yu; University of Rochester | | |
| | Stanislava Soro; University of Rochester | | |
| | Gaurav Sharma; University of Rochester | | |
| | Wendi Heinzelman; University of Rochester | | |
| Abstract: |
We examine the trade-off between lifetime and distortion in image sensor networks deployed for gathering visual information over a monitored region. Users navigate over the monitored region by specifying a viewpoint that varies with time, and the network attempts to meet the user requirement by synthesizing the desired view using a selection of cameras. We compare two camera selection methods, the first maximizes PSNR for the user's view without considering the cameras' available energy whereas the second uses knowledge of available energy at the cameras to maximize network lifetime. Our simulation results demonstrate a clear trade-off between the two strategies, with selection based on energy alone performing up to 3 dB worse initially than the PSNR based selection yet providing significantly higher coverage lifetime. In addition, we observe that under a fixed total energy constraint, more cameras with lower energy per node are preferable over fewer cameras with higher energy per node. Our results suggest that a hybrid or adaptive camera selection algorithm may provide the optimal lifetime-distortion trade-off. |
