Paper
13 September 2008 Exploiting spatio-temporal characteristics of human vision for mobile video applications
Author Affiliations +
Abstract
Video applications on handheld devices such as smart phones pose a significant challenge to achieve high quality user experience. Recent advances in processor and wireless networking technology are producing a new class of multimedia applications (e.g. video streaming) for mobile handheld devices. These devices are light weight and have modest sizes, and therefore very limited resources - lower processing power, smaller display resolution, lesser memory, and limited battery life as compared to desktop and laptop systems. Multimedia applications on the other hand have extensive processing requirements which make the mobile devices extremely resource hungry. In addition, the device specific properties (e.g. display screen) significantly influence the human perception of multimedia quality. In this paper we propose a saliency based framework that exploits the structure in content creation as well as the human vision system to find the salient points in the incoming bitstream and adapt it according to the target device, thus improving the quality of new adapted area around salient points. Our experimental results indicate that the adaptation process that is cognizant of video content and user preferences can produce better perceptual quality video for mobile devices. Furthermore, we demonstrated how such a framework can affect user experience on a handheld device.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rashad Jillani and Hari Kalva "Exploiting spatio-temporal characteristics of human vision for mobile video applications", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70730N (13 September 2008); https://doi.org/10.1117/12.796746
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Video

Video surveillance

Mobile devices

Image processing

Video processing

Video compression

Scalable video coding

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