By Luisa M. Regueras, María Jesús Verdú, Rafael Mompó (auth.), Tat-Jen Cham, Jianfei Cai, Chitra Dorai, Deepu Rajan, Tat-Seng Chua, Liang-Tien Chia (eds.)
The quantity set LNCS 4351 and LNCS 4352 constitutes the refereed lawsuits of the thirteenth foreign Multimedia Modeling convention, MMM 2007, held in Singapore in January 2007.
Based on rigorous reviewing, this system committee chosen 123 rigorously revised complete papers of the most technical periods and 33 revised complete papers of 4 precise periods from a complete of 392 submissions for presentation in volumes.
The first quantity comprises seventy six contributions. They contain assurance of issues concerning studying semantic ideas, photographs, snapshot registration, matching and texture, human-computer interplay, monitoring and movement research, complex media coding and model, media annotation, snapshot and video coding, context-aware media modeling, multimedia databases, and photo processing.
The moment quantity collects eighty papers. They contain insurance of subject matters concerning multimedia sign processing and communications, occasion detection, multimedia over P2P, content material, functions, computing device imaginative and prescient, picture processing, multimedia sign processing and communications, picture class and popularity, complicated media processing and protection, and ubiquitous
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Extra resources for Advances in Multimedia Modeling: 13th International Multimedia Modeling Conference, MMM 2007, Singapore, January 9-12, 2007. Proceedings, Part II
In section 3, we will define the visual information and give the quantitative metric of system performance. In section 4, we will present the rate allocation scheme based on section 3 and analyze the simulation results. Finally, section 5 concludes the paper. 2 System Models In this section, some system models are given to formulate the optimal problem. We first introduce the DVC rate distortion model based on Slepian-Wolf and Wyner-Ziv theorem [6,7]. And following, base on the DVC rate distortion model, the expression of visual information of a video frame is given.
M. W. Marcellin and T. R. Fischer, “Trellis Coded Quantization of Memoryless and Gauss-Markov Sources,” IEEE Trans. , vol. 38, pp. 82–93, Jan. 1990. 6. G. Ungerboeck, “Channel coding with multilevel/phase signals” IEEE Trans. Inform. Theory, vol. IT-28, pp. 55–67, Jan. 1982. 7. S. S. Pradhan and K. Ramchandran, “Distributed source coding using syndromes (DISCUS): design and construction,” Proceedings of the Data Compression Conference (DCC), March, Snowbird, UT, 1999. 8. Y. Yang, S. Cheng, Z. Xiong, and W.
These frequencies and voltages are determined in such a way that a frame belonging to the scenario still meets its deadline while minimizing the decoder’s energy consumption. , the client is ‘calibrated’, video streams can be sent to the client and the client will adjust the frequency and voltage levels per frame according to the scenario the frame belongs to. The overall goal is to reduce the energy consumption while meeting the deadlines. Note that the calibration step needs to be done only once for a given client.
Advances in Multimedia Modeling: 13th International Multimedia Modeling Conference, MMM 2007, Singapore, January 9-12, 2007. Proceedings, Part II by Luisa M. Regueras, María Jesús Verdú, Rafael Mompó (auth.), Tat-Jen Cham, Jianfei Cai, Chitra Dorai, Deepu Rajan, Tat-Seng Chua, Liang-Tien Chia (eds.)