ACM Transactions on Multimedia Computing, Communications and by James R. Wilcox

By James R. Wilcox

This designated factor contains a few of the impressive paintings initially offered on the ACM Multimedia convention 2003 (ACM MM 2003). The convention acquired 255 submissions, of which forty three high quality papers have been accredited for presentation. of those papers, the Technical software Chairs invited a dozen authors to put up superior models in their papers to this distinctive factor. those papers went via a rigorous overview strategy, and we're satisfied to offer 4 actually extraordinary papers during this specialissue. as a result hugely aggressive review method and restricted house, many glorious papers couldn't be accredited for this distinct factor. even though, a few of them are being forwarded for attention as destiny ordinary papers during this magazine.

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Additional info for ACM Transactions on Multimedia Computing, Communications and Applications (May)

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85 This table shows the performance of the sensors compressing a single image repeatedly with no video capture. Table III. Standalone Optimized vs. 72 This table shows the additional overhead incurred by the sensor in both capturing and compressing video. approximately 10 frames per second using a high-quality image. It should be noted that the compression times using the IPP are dependent on the actual video content. In comparing the two platforms, it appears that the Stargate platform is able to outperform the Bitsy platform using the Intel Performance Primitives but cannot outperform it using the software compression algorithm.

Comput. Syst. (May). , AND WASSERMAN, K. 2001. Fugue: Time scales of adaptation in mobile video. ). , AND ESTRIN, D. 1999. RAP: An end-to-end rate-based congestion control mechanism for real time streaming in the internet. In Proceedings of INFOCOM 1999. , AND SUKHATME, G. 1992. Connecting the physical world with pervasive networks. IEEE Perv. Comput. ), 59–69. , AND PRABHUDEV, A. 1999. A priority-based technique for the best effort delivery of stored video. In Proceedings of the ACM/SPIE Multimedia Computing and Networking Conference.

Clearly, advances in these areas can be incorporated into our video sensor technology. 3 Mobile Power Management Mobile power management is another key problem for long-lived video sensors. There have been many techniques focused on overall system power management. Examples include the work being done by Kravets at UIUC [Kravets and Krishnan 2000], Noble at the University of Michigan [Corner et al. 2001], and Satyanarayanan at CMU [Flinn and Satyanarayanan 1999]. We have not yet implemented power management routines within the video platform.

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