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This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ACM Transactions on Information Systems, http://dx.doi.org/10.1145/1961209.1961214 ; We present a model for exploiting community-based usage information for video retrieval, where implicit usage information from past users is exploited in order to provide enhanced assistance in video retrieval tasks, and alleviate the effects of the semantic gap problem. We propose a graph-based model for all types of implicit and explicit feedback, in which the relevant usage information is represented. Our model is designed to capture the complex interactions of a user with an interactive video retrieval system, including the representation of sequences of user-system interaction during a search session. Building upon this model, four recommendation strategies are defined and evaluated. An evaluation strategy is proposed based on simulated user actions, which enables the evaluation of our recommendation strategies over a usage information pool obtained from 24 users performing four different TRECVid tasks. Furthermore, the proposed simulation approach is used to simulate usage information pools with different characteristics, with which the recommendation approaches are further evaluated on a larger set of tasks, and their performance is studied with respect to the scalability and quality of the available implicit information. ; This work was partially supported by the Spanish Ministry of Science and Education (TIN2008-06566-C04-02) and the Regional Government of Madrid (S2009TIC-1542). F. Hopfgartner was supported by a postdoctoral fellowship of the German Academic Exchange Service (DAAD)

Video de-interlacing algorithms perform a crucial task in video processing. Despite these algorithms are developed using software implementations, their implementations in hardware are required to achieve real-time operation. This paper describes the development of an embedded system for video de-interlacing. The algorithm for video de-interlacing uses three fuzzy logic-based systems to tackle three relevant features in video sequences: motion, edges, and picture repetition. The proposed strategy implements the algorithm as a hardware IP core on a FPGA-based embedded system. The paper details the proposed architecture and the design methodology to develop it. The resulting embedded system is verified on a FPGA development board and it is able to de-interlace in real-time. © 2013 Elsevier B.V. All rights reserved. ; This work was partially supported by MOBY-DIC project FP7-INFSO-ICT-248858 (www.mobydic-project.eu) from EuropeanCommunity, TEC2011-24319 project from the Spanish Govern-ment, and P08-TIC-03674 project from the Andalusian Regional Government (with support from the PO FEDER). P. Brox is supportedunder the post-doctoral program called 'Juan de la Cierva' from theSpanish Ministry of Science and Innovation. ; Peer Reviewed