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         author = {Anemueller, Joern and Back, Joerg-Henrik and Caputo, Barbara and Luo, Jie and Ohl, Frank and Orabona, Francesco and Vogels, Rufin and Weinshall, Daphna and Zweig, Alon},
       projects = {Idiap, DIRAC},
          title = {Biologically Motivated Audio-Visual Cue Integration for Object},
      booktitle = {Proceedings of the first Internatinal Conference on Cognitive Systems},
           year = {2008},
       abstract = {Auditory and visual cues are important sensor
inputs for biological and artificial systems. They provide
crucial information for navigating environments, recognizing
categories, animals and people. How to combine effectively
these two sensory channels is still an open issue. As a step
towards this goal, this paper presents a comparison between
three different multi-modal integration strategies, for audiovisual
object category detection. We consider a high-level and a
low-level cue integration approach, both biologically motivated,
and we compare them with a mid-level cue integration scheme.
All the three integration methods are based on the least
square support vector machine algorithm, and state of the
art audio and visual feature representations. We conducted
experiments on two audio-visual object categories, dogs and
guitars, presenting different visual and auditory characteristics.
Results show that the high-level integration scheme consistently
performs better than single cue methods, and of the other
two integration schemes. These findings confirm results from
the neuroscience. This suggests that the high-level integration
scheme is the most suitable approach for multi-modal cue
integration for artificial cognitive systems.},
            pdf = {https://publications.idiap.ch/attachments/papers/2008/Anemueller_ICCS2008_2008.pdf}