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Jan Jastorff, Zoe Kourtzi, Martin A Giese; Role of learning in biological motion recognition. Journal of Vision 2003;3(9):84. doi: 10.1167/3.9.84.
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© ARVO (1962-2015); The Authors (2016-present)
It has been shown, that humans can learn to discriminate between different styles of natural movements (e.g. gaits or sports movements). However, it remains unknown whether this learning is based on ‘innate’ templates for biological movement patterns, or if humans can learn new representations of arbitrary complex movements. We address this question by investigating, whether subjects can learn novel artificial biological movement stimuli. These stimuli were generated by linearly combining prototypical trajectories of very dissimilar natural movements in space-time using spatio-temporal morphable models (Giese & Poggio, 2000). Most of the tested stimuli do not correspond to naturally occurring movements, and some of them likely even violate the physical laws of human body movement. Subjects had to discriminate between pairs of these stimuli, containing slightly different weights of the prototypes. The stimuli were presented as standard point light walker (PLW), and as point light walker with position jitter (generated by adding random displacements of the dots along the skeleton of the walker for every frame). Subjects trained with standard PLW learned relatively quickly (after about 8 trails) to discriminate between these stimuli. Testing different subjects with stimuli that were rotated by 90 deg in the image plane showed that the learned representation transferred to rotated stimuli. Subjects that were trained with PLW with position jitter learned the discrimination task equally fast (8 trials). However, another set of subjects trained with the same stimuli and tested with rotated stimuli did not show transfer of the learned discrimination to rotated stimuli. We draw the following conclusions from this experiment: (1) New templates for biological movement recognition can be acquired very quickly. (2) Learning affects at least two different levels of representation (local and holistic). (3) The learned holistic representations seem to be view-dependent.
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