Gaze-contingent visual communication
Gaze-contingent visual communication
User performance with gaze contingent multiresolutional displays
ETRA '00 Proceedings of the 2000 symposium on Eye tracking research & applications
Eye Tracking Methodology: Theory and Practice
Eye Tracking Methodology: Theory and Practice
DANCE '02 Proceedings of the 2002 DARPA Active Networks Conference and Exposition
Predictive perceptual compression for real time video communication
Proceedings of the 12th annual ACM international conference on Multimedia
Rate scalable video coding using a foveation-based human visual system model
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Foveated video compression with optimal rate control
IEEE Transactions on Image Processing
Predictive real-time perceptual compression based on eye-gaze-position analysis
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
An empirical pipeline to derive gaze prediction heuristics for 3D action games
ACM Transactions on Applied Perception (TAP)
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Human eyes have limited perception capabilities. Only 2 degrees of our 180 degree vision field provide the highest quality of perception. Due to this fact the idea of perceptual attention focus emerged to allow a visual content to be changed in a way that only part of the visual field where a human attention is directed to is encoded with a high quality. The image quality in the periphery can be reduced without a viewer noticing it. This compression approach allows a significant decrease in bit-rate for a video stream, and in the case of the 3D stream rendering, it decreases the computational burden. A number of previous researchers have investigated the topic of real-time perceptual attention focus but only for a single viewer. In this paper we investigate a dynamically changing multi-viewer scenario. In this type of scenario a number of people are watching the same visual content at the same time. Each person is using eye-tracking equipment. The visual content (video, 3D stream) is sent through a network with a large transmission delay. The area of the perceptual attention focus is predicted for the viewers to compensate for the delay value and identify the area of the image which requires highest quality coding.