Download Adaptive Multimedia Retrieval:User, Context, and Feedback: by Stéphane Marchand-Maillet, Eric Bruno PDF

By Stéphane Marchand-Maillet, Eric Bruno

This e-book constitutes the completely refereed post-proceedings of the 4th foreign Workshop on Adaptive Multimedia Retrieval, AMR 2006, held in Geneva, Switzerland in July 2006.

The 18 revised complete papers awarded including 2 invited papers have been rigorously chosen in the course of rounds of reviewing and development. additionally integrated are invited contributions which have been meant to open on less-addressed subject matters in the neighborhood, because it is the case for track details retrieval and dispensed details retrieval. The papers are equipped in topical sections on ontology-based retrieval and annotation, score and similarity measurements, track info retrieval, visible modelling, adaptive retrieval, structuring multimedia, in addition to person integration and profiling.

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Additional resources for Adaptive Multimedia Retrieval:User, Context, and Feedback: 4th International Workshop, AMR 2006, Geneva, Switzerland, July, 27-28, 2006, Revised ... Applications, incl. Internet/Web, and HCI)

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4 – and can be used in a query process to determine similarity between different regions of different images. In a subsequent step, newly added or existing regions can be enriched by adding annotations describing the semantics of a region. The user can select 24 C. Hentschel et al. regions through the annotation tool and attach keyword lists to each of them. As the image as a whole can be seen as a region as well, a global image annotation can be attached likewise. Typically, an image can be split into atomic regions representing the smallest semantic entities.

Structure of a video is generally analyzed in terms of objects and events. We introduce concept (complex event series) as the new modeling component. Low-level features and spatial/spatio-temporal relationships between objects and events constitute the concept layer (Fig. 1). Temporal knowledge like ordering operations and spatio-temporal relations between objects are used to define events and concepts. Fig. 1. Component Layers of Video Sources Ontology-Supported Video Modeling and Retrieval 31 Objects, events, concepts, low-level features, spatio-temporal knowledge and fuzziness are the main and auxiliary modeling components of this video model.

Stauffer and W. E. L. Grimson. Adaptive background mixture models for realtime tracking. In Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pages 246–252, 1999. 31. R. C. Veltkamp and M. Tanase. Content-based image retrieval systems: A survey. , Utrecht University, 2000. 32. N. Voisine, S. Dasiopoulou, F. Precioso, V. Mezaris, I. Kompatsiaris, and M. Strintzis. A genetic algorithm-based approach to knowledge-assisted video analysis. In IEEE International Conference on Image Processing, 2005.

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