As plain as the noise on your face: Adaptive video compression using face detection and visual eccentricity models

Sensitivity and resolution reduction as a function of eccentricity account for one of the largest sources of compression in vision. However, utilization of this visual property has been limited to systems that directly measure the viewer’s gaze position. We have applied visual eccentricity models to videophone compression applications without using eye tracking by combining the visual model with a face tracking algorithm. In lieu of a gaze detector, we assume the gaze will be directed to the faces appearing in images. The incorporation of resolution as well as sensitivity-based eccentricity models in a low bit rate video-compression standard (H.263) will be discussed. For videophone applications, we achieve up to a 50% reduction in bit rate while retaining similar image quality. Problems arising from the increased temporal sensitivity of the periphery, despite its reduced spatial bandwidth, are also discussed.