Paper
14 March 2005 Adaptive multifoveation for low-complexity video compression with a stationary camera perspective
Sriram Sankaran, Rashid Ansari, Ashfaq A. Khokhar
Author Affiliations +
Proceedings Volume 5685, Image and Video Communications and Processing 2005; (2005) https://doi.org/10.1117/12.588114
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Abstract
In human visual system the spatial resolution of a scene under view decreases uniformly at points of increasing distance from the point of gaze, also called foveation point. This phenomenon is referred to as foveation and has been exploited in foveated imaging to allocate bits in image and video coding according to spatially varying perceived resolution. Several digital image processing techniques have been proposed in the past to realize foveated images and video. In most cases a single foveation point is assumed in a scene. Recently there has been a significant interest in dynamic as well as multi-point foveation. The complexity involved in identification of foveation points is however significantly high in the proposed approaches. In this paper, an adaptive multi-point foveation technique for video data based on the concepts of regions of interests (ROIs) is proposed and its performance is investigated. The points of interest are assumed to be centroid of moving objects and dynamically determined by the foveation algorithm proposed. Fast algorithm for implementing region based multi-foveation processing is proposed. The proposed adaptive multi-foveation fully integrates with existing video codec standard in both spatial and DCT domain.
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Sriram Sankaran, Rashid Ansari, and Ashfaq A. Khokhar "Adaptive multifoveation for low-complexity video compression with a stationary camera perspective", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005); https://doi.org/10.1117/12.588114
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Cited by 4 scholarly publications.
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KEYWORDS
Video

Computer programming

Image compression

Video coding

Video compression

Image quality

Image resolution

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