Real-Time Probabilistic Tracking of Faces in Video
ICIAP '09 Proceedings of the 15th International Conference on Image Analysis and Processing
Foveated mean squared error--a novel video quality metric
Multimedia Tools and Applications
Efficient video coding based on audio-visual focus of attention
Journal of Visual Communication and Image Representation
| Hi-index | 0.00 |
We present a Bayesian model that allows to automatically generate flxations/foveations and that can be suitably exploited for compression purposes. The twofold aim of this work is to investigate how the exploitation of high-level perceptual cues provided by human faces occurring in the video can enhance the compression process without reducing the perceived quality of the video and to validate such assumption with an extensive and principled experimental protocol. To such end, the model integrates top-down and bottom-up cues to choose the fixation point on a video frame: at the highest level, a fixation is driven by prior information and by relevant objects, namely human faces, within the scene; at the same time, local saliency together with novel and abrupt visual events contribute by triggering lower level control. The performance of the resulting video compression system has been evaluated with respect to both the perceived quality of foveated video clips and the compression gain with an extensive evaluation campaign, which has eventually involved 200 subjects.