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ICANN
2005
Springer

Learning Features of Intermediate Complexity for the Recognition of Biological Motion

9 years 3 months ago
Learning Features of Intermediate Complexity for the Recognition of Biological Motion
Humans can recognize biological motion from strongly impoverished stimuli, like point-light displays. Although the neural mechanism underlying this robust perceptual process have not yet been clarified, one possible explanation is that the visual system extracts specific motion features that are suitable for the robust recognition of both normal and degraded stimuli. We present a neural model for biological motion recognition that learns robust mid-level motion features in an unsupervised way using a neurally plausible memory-trace learning rule. Optimal mid-level features were learnt from image motion sequences containing a walker with, or without background motion clutter. After learning of the motion features, the detection performance of the model substantially increases, in particular in presence of clutter. The learned mid-level motion features are characterized by horizontal opponent motion, where this feature type arises more frequently for the training stimuli without motion c...
Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Marti
Added 27 Jun 2010
Updated 08 Jul 2010
Type Conference
Year 2005
Where ICANN
Authors Rodrigo Sigala, Thomas Serre, Tomaso Poggio, Martin A. Giese
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