DIRAC

Detection and identification of rare audio-visual events

Jörn Anemüller, Barbara Caputo, Hynek Hermansky, Frank W. Ohl, Tomas Pajdla, Misha Pavel, Luc Van Gool, Rufin Vogels, Stefan Wabnik, Daphna Weinshall

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The DIRAC project was an integrated project that was carried out between January 1 st 2006 and December 31 st 2010. It was funded by the European Commission within the Sixth Framework Research Programme (FP6) under contract number IST-027787. Ten partners joined forces to investigate the concept of rare events in machine and cognitive systems, and developed multi-modal technology to identify such events and deal with them in audio-visual applications. This document summarizes the project and its achievements. In Section 2 we present the research and engineering problem that the project set out to tackle, and discuss why we believe that advance made on solving these problems will get us closer to achieving the general objective of building artificial cognitive system with cognitive capabilities. We describe the approach taken to solving the problem, detailing the theoretical framework we came up with. We further describe how the inter-disciplinary nature of our research and evidence collected from biological and cognitive systems gave us the necessary insights and support for the proposed approach. In Section 3 we describe our efforts towards system design that follow the principles identified in our theoretical investigation. In Section 4 we describe a variety of algorithms we have developed in the context of different applications, to implement the theoretical framework described in Section 2. In Section 5 we describe algorithmic progress on a variety of questions that concern the learning of those rare events as defined in our Section 2. Finally, in Section 6 we describe our application scenarios, an integrated test-bed developed to test our algorithms in an integrated way.

Original languageEnglish (US)
Title of host publicationStudies in Computational Intelligence
Pages3-35
Number of pages33
Volume384
DOIs
StatePublished - 2012

Publication series

NameStudies in Computational Intelligence
Volume384
ISSN (Print)1860949X

Fingerprint

Cognitive systems
Biological systems
Systems analysis

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Anemüller, J., Caputo, B., Hermansky, H., Ohl, F. W., Pajdla, T., Pavel, M., ... Weinshall, D. (2012). DIRAC: Detection and identification of rare audio-visual events. In Studies in Computational Intelligence (Vol. 384, pp. 3-35). (Studies in Computational Intelligence; Vol. 384). https://doi.org/10.1007/978-3-642-24034-8_1

DIRAC : Detection and identification of rare audio-visual events. / Anemüller, Jörn; Caputo, Barbara; Hermansky, Hynek; Ohl, Frank W.; Pajdla, Tomas; Pavel, Misha; Van Gool, Luc; Vogels, Rufin; Wabnik, Stefan; Weinshall, Daphna.

Studies in Computational Intelligence. Vol. 384 2012. p. 3-35 (Studies in Computational Intelligence; Vol. 384).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Anemüller, J, Caputo, B, Hermansky, H, Ohl, FW, Pajdla, T, Pavel, M, Van Gool, L, Vogels, R, Wabnik, S & Weinshall, D 2012, DIRAC: Detection and identification of rare audio-visual events. in Studies in Computational Intelligence. vol. 384, Studies in Computational Intelligence, vol. 384, pp. 3-35. https://doi.org/10.1007/978-3-642-24034-8_1
Anemüller J, Caputo B, Hermansky H, Ohl FW, Pajdla T, Pavel M et al. DIRAC: Detection and identification of rare audio-visual events. In Studies in Computational Intelligence. Vol. 384. 2012. p. 3-35. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-642-24034-8_1
Anemüller, Jörn ; Caputo, Barbara ; Hermansky, Hynek ; Ohl, Frank W. ; Pajdla, Tomas ; Pavel, Misha ; Van Gool, Luc ; Vogels, Rufin ; Wabnik, Stefan ; Weinshall, Daphna. / DIRAC : Detection and identification of rare audio-visual events. Studies in Computational Intelligence. Vol. 384 2012. pp. 3-35 (Studies in Computational Intelligence).
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