INTRODUCTION Global illumination is the physically accurate calculation of lighting in an environment. It is computationally expensive for static environments and even more so for dynamic environments. Not only are many images required for an animation, but the calculation involved increases with the presence of moving objects. In static environments, global illumination algorithms can precompute a lighting solution and reuse it whenever the viewpoint changes, but in dynamic environments, any moving object or light potentially affects the illumination of every other object in a scene. To guarantee accuracy, the algorithm has to recompute the entire lighting solution for each frame. This paper describes a perceptually-based technique that can dramatically reduce this computational load. The technique may also be used in image based rendering, geometry level of detail selection, realistic image synthesis, video telephony and video compression. Perceptually-based rendering operat

this paper In this paper, we implementfoveation ltering having low pass lters with continuously varying cuto frequencies. For discrete images, we are forced to use a xed set of cuto frequencies, yet, unlike the WT or the STFT, we allow for an arbitrary cuto frequency. Using such low pass lters, the performance of the algorithm does not depend on the cuto frequency (as in the WT). As long as the local bandwidth transition is monotonically changed, position-varying lowpass ltering can be utilized to compute foveated images that better approximate the human visual system. Another merit of this approach is computational simplicity (easy implementation) and adaptiveinterface with standard video

Approximately 2 degrees in our 140 degree vision span has sharp vision. Many researchers have been fascinated by the idea of eyetracking integrated perceptual compression of an image or video, yet any practical system has yet to emerge. The unique challenge presented by real time perceptual video streaming is how to handle the fast nature of the human eye and provide its integration with computationally intensive video transcoding scheme. The delay introduced by video transmission in the network presents a difficulty. This delay creates a problem when we try to use information about eye movements for perceptual encoding. In this paper we discuss a new approach to the eyetracker based video compression. Rather than relying on the point of gaze, this novel scheme tracks a vicinity of interest and offers a prediction mechanism for eye movements. The described system compensates the interim eye movements between the sampling and actual coding. The proposed scheme can be applied to a large variety of today’s video compression standards. We have developed an eye gaze-aware MPEG-2 transcoder that can perceptually re-encode a live video stream in real time. The experiments we have conducted illustrate the substantial impact this integrated prediction method has on perceptual video compression and bit-rate reduction.