%Aigaion2 BibTeX export from Idiap Publications
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@TECHREPORT{Anemueller_Idiap-RR-41-2010,
         author = {Anemueller, Joern and Back, Joerg-Henrik and Caputo, Barbara and havlena, michal and Luo, Jie and Kayser, Hendrik and Leibe, Bastian and Motlicek, Petr and Pajdla, Tomas and Pavel, Misha and Torii, Akihiko and Gool, Luc Van and Hermansky, Hynek and Zweig, Alon},
       projects = {Idiap, DIRAC},
          month = {11},
          title = {The DIRAC AWEAR Audio-Visual Platform for Detection of Unexpected and Incongruent Events},
           type = {Idiap-RR},
         number = {Idiap-RR-41-2010},
           year = {2010},
    institution = {Idiap},
       abstract = {It is of prime importance in everyday human life to cope with and
respond appropriately to events that are not foreseen by prior
experience. Machines to a large extent lack the ability to respond
appropriately to such inputs. An important class of unexpected
events is defined by incongruent combinations of inputs from
different modalities and therefore multimodal information
provides a crucial cue for the identification of such events, e.g.,
the sound of a voice is being heard while the person in the fieldof-
view does not move her lips. In the project DIRAC ({\^{a}}€{\oe}Detection
and Identification of Rare Audio-visual Cues{\^{a}}€) we have been
developing algorithmic approaches to the detection of such
events, as well as an experimental hardware platform to test it. An
audio-visual platform ({\^{a}}€{\oe}AWEAR{\^{a}}€ {\^{a}}€“ audio-visual wearable
device) has been constructed with the goal to help users with
disabilities or a high cognitive load to deal with unexpected
events. Key hardware components include stereo panoramic
vision sensors and 6-channel worn-behind-the-ear (hearing aid)
microphone arrays. Data have been recorded to study audio-visual
tracking, a/v scene/object classification and a/v detection of
incongruencies.},
            pdf = {https://publications.idiap.ch/attachments/reports/2008/Anemueller_Idiap-RR-41-2010.pdf}
}