Publications on self-organizing networked systems

The Video Browser Showdown (VBS) is a live video browsing competition where international researchers, working in the field of interactive video search, evaluate and demonstrate the efficiency of their tools in presence of the audience. The aim of the VBS is to evaluate video browsing tools for efficiency at known-item search (KIS) tasks with a well-defined data set in direct comparison to other tools. For each task the moderator presents a target clip on a shared screen that is visible to all participants.

The Video Browser Showdown (VBS) 2012 showed that certain Known-Item- Search (KIS) tasks can be performed effectively and efficiently with our AAU Video Browser[1]. It is solely based on intelligent interaction means and refrains from content analysis, but it takes use of the human abilities to recognize and classify items very fast. Therefore, scenes that are significantly different from the other scenes in a video or scenes that are expected at certain locations of a video.

This paper describes our contribution to the social event detection (SED) task of the MediaEval Benchmark 2013. We present a robust unsupervised approach for the clustering of tagged photos and videos into social events. Results on the SED datasets show that the proposed approach yields an excellent generalization ability and state-of-the-art clustering performance.

Abstract—We present a novel interface for large-scale video archives that uses content-based filtering of search results. The interface has been used for the Interactive Known-Item Search (Interactive KIS) task of TRECVID 2012 and achieved good search performance. We found that for KIS tasks contentbased filtering as used in our interface is convenient and able to successfully narrow down interactive search for many of the TRECVID KIS queries used in

2012.

W. Elmenreich, R. D'Souza, C. Bettstetter, and H. de Meer. A survey of models and design methods for self-organizing networked systems. In Proceedings of the Fourth International Workshop on Self-Organizing Systems.

W. Elmenreich, T. Ibounig, and I. Fehérvári. Robustness versus performance in sorting and tournament algorithms. In Acta Polytechnica. Vol. 6, No. 5, pages 7–18, ISSN 1785-8860, 2009

I. Fehérvári and W. Elmenreich. Evolving neural network controllers for a team of self-organizing robots. In Journal of Robotics. Hindawi, 2010

A. Sobe, W. Elmenreich, and L. Böszörmenyi. Towards a Self-Organizing Replication Model for Non-Sequential Media Access. ACM Multimedia 2010 Workshop - Social, Adaptive and Personalized Multimedia Interaction and Access, SAPMIA 2010

W. Elmenreich and I. Fehérvári. Evolving self-organizing cellular automata based on neural network genotypes. In C. Bettstetter, C. Gershenson, editor, Proceedings of the Fifth International Workshop on Self-Organizing Systems.

A. Sobe, W. Elmenreich, and L. Böszörmenyi. Replication for bio-inspired delivery in unstructured peer-to-peer networks. In Proceedings of the Ninth International Workshop on Intelligent Solutions in Embedded Systems, Regensburg, Germany, July 201