Advances in Multimedia Modeling: 13th International by Luisa M. Regueras, María Jesús Verdú, Rafael Mompó (auth.),

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 complaints of the thirteenth overseas Multimedia Modeling convention, MMM 2007, held in Singapore in January 2007.

Based on rigorous reviewing, this system committee chosen 123 conscientiously revised complete papers of the most technical classes and 33 revised complete papers of 4 particular classes from a complete of 392 submissions for presentation in volumes.

The first quantity comprises seventy six contributions. They contain insurance of subject matters regarding studying semantic innovations, portraits, photograph 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 photograph processing.

The moment quantity collects eighty papers. They contain insurance of issues concerning multimedia sign processing and communications, occasion detection, multimedia over P2P, content material, purposes, desktop imaginative and prescient, photo processing, multimedia sign processing and communications, photo class and popularity, complex media processing and protection, and ubiquitous

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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. We now discuss how the client is to be profiled for filling in the scenario adaptation table. We subsequently detail on the scenario-driven decoding. 1 Client Profiling In order to enable client profiling, the content provider needs to determine a scenario representative for each scenario, see Fig.

Hughes et al. [10] present an energy reduction approach that consists of two phases. First, a profiling phase determines for each possible configuration the maximum ‘budget’ of instructions for processing a given frame type without missing the deadline. The number of instructions needed for the next frame is predicted and the hardware configuration that will minimize energy consumption without missing the deadline is installed. A similar approach was proposed by Choi et al. [14]. Another approach to client-side energy-efficient decoding is by using controltheoretic feedback-control mechanisms as proposed by Lu et al.

Wu-chi Feng, Brian Code, Ed Kaiser, Mike Shea, Wu-chang Feng, Louis Bavoil, Panoptes: Scalable Low-Power Video Sensor Networking Technologies, ACM Transactions on Multimedia Computing, Communications and Applications, January 2005. 12. Zhihai He, Yongfang Liang, Lulin Chen, Ishfaq Ahmad, and Dapeng Wu, Power-rate-distortion analysis for wireless video communication under energy constraint, IEEE Trans. Circuits Syst. , vol. 15, no. 5, pp. 645–658,. May. 2005. R. R. com Abstract. In conventional video coding systems, the encoder performs predictive coding (motion estimation) to exploit the temporal similarity, which make its complexity much higher than that of the decoder.

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