By Stephane Marchand-Maillet, Donn Morrison, Eniko Szekely, Jana Kludas, Marc Vonwyl (auth.), Marcin Detyniecki, Ana García-Serrano, Andreas Nürnberger (eds.)

This ebook constitutes the refereed lawsuits of the seventh foreign convention on Adaptive Multimedia Retrieval, AMR 2009, held in Madrid, Spain, in September 2009.The 12 revised complete papers and the invited contribution offered have been conscientiously reviewed. The papers are geared up in topical sections on greedy multimedia streams; pinpointing song; adapting distances; knowing pictures; and round the user.

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Additional resources for Adaptive Multimedia Retrieval. Understanding Media and Adapting to the User: 7th International Workshop, AMR 2009, Madrid, Spain, September 24-25, 2009, Revised Selected Papers

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For efficiency, IVOnLA performs global motion estimation simultaneously to motion objects segmentation, via an iterative fitting scheme. There are many reported approaches to moving objects segmentation in the compressed domain [18][19][20]. The technique implemented in the IVOnLA is based on an efficient approach described in [18], in which robust dominant motion estimation and temporal coherence constraints are used to separate moving objects from the background. In order to improve the segmentation results of this technique several modifications over the base algorithm were proposed [21], namely a new scheme to better handle the intra-coded macroblocks, an improved mechanism to exploit the temporal coherence of the objects, a procedure to refine the motion masks with the colour information, and some initial ideas to handle dynamic backgrounds.

Ewert, M. B. Dannenberg in the score domain can be translated into a query in the audio domain, which can be used in an underlying audio retrieval system. This way, the user can make use of a semantically oriented high-level representation while the low-level representation needed only for technical reasons is hidden from the user. In general terms, music synchronization denotes a procedure which, for a given position in one representation of a piece of music, determines the corresponding position within another representation.

This procedure is repeated until either the score of an optimal path or the size of a submatrix is below a given threshold. This results in a monotonic alignment set in form of a family of paths F . Fig. 2e shows a family of two paths derived from the score Towards Reliable Partial Music Alignments 41 matrix in Fig. 2b using our recursive Smith-Waterman variant. Here, the missing bridge in the audio as well as the different intros and outros in the audio and MIDI version are detected and, in this example, the recursive Smith-Waterman approach avoids a misalignment as in the DTW case (Fig.

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