| Paper: | MSP-P1.10 | ||
| Session: | Human Machine Interface; Signal Processing for Media Integration and Application | ||
| Time: | Friday, May 21, 09:30 - 11:30 | ||
| Presentation: | Poster | ||
| Topic: | Multimedia Signal Processing: Multimedia Applications | ||
| Title: | PROBABILISTIC FACE RECOGNITION FROM COMPRESSED IMAGERY | ||
| Authors: | Jian Li; University of Maryland, College Park | ||
| Shaohua Zhou; University of Maryland, College Park | |||
| Abstract: | The effects of image and video compression on face recognition in the still-to-video setting are studied in this paper. We use the probabilistic framework described in [8], which solves tracking and recognition problems simultaneously via sequential importance sampling (SIS). To account for the illumination and pose variations in test sequences, intrapersonal space (IPS) isconstructed from examplar views and used to calculate the likelihood density. Both the gallery images and probe videos arecompressed and several experiments are run to study their effects on the recognition rate. Some useful conclusions are drawn from the analysis of the experimental results, which will be helpful for future research on the interaction between recognition and compression. Meanwhile, the experiments also demonstrate the robustness of the proposed methods. | ||
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