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Learning of Articial Biological Motion: A Comparison Between Natural and Synthetic Trajectories

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84832

Jastorff,  J
Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84023

Kourtzi,  Z
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84787

Giese,  MA
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Citation

Jastorff, J., Kourtzi, Z., & Giese, M. (2003). Learning of Articial Biological Motion: A Comparison Between Natural and Synthetic Trajectories. Poster presented at 6. Tübinger Wahrnehmungskonferenz (TWK 2003), Tübingen, Germany.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-DD16-E
Abstract
It has been shown, that humans are able to learn to discriminate between dierent 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 representations of new arbitrary complex movements. We address this question by investigating whether subjects can learn articial biological movement stimuli. Methods: We generated biological motion stimuli by linear combination of prototypical trajectories. Spatio-temporal linear combinations were computed using special algorithm, spatio-temporal morphable model (Giese Poggio, 2000, International Journal of Computer Vision, 59-73). The following two classes of stimuli were generated: (A) stimuli derived by linear combination of dissimilar natural movements (e.g., walking, kicking and dancing). (B) Stimuli generated by animation of an articial skeleton model that is highly dissimilar from naturally occurring body structures. The joint angle trajectories of the skeleton were given by linear combinations of synthetic trajectories. These trajectories were sinusoidal functions. Their amplitudes and frequencies were approximately matched with the joint trajectories of human actors during natural movements. Subjects had to discriminate between pairs of these stimuli that were dened by linear combinations with slightly dissimilar weights. The trajectories were presented as normal point light walkers (PLW), and as point light walker with position jitter (PLWJ). The PLWJ were generated by adding random displacements of the dots along the skeleton of the walker for in each frame. Each subject took part in two training and three test blocks. Feedback was provided only during training. Results: Subjects trained with stimuli derived from natural movements (group A) learned the discrimination between novel patterns very quickly (about 8 repetitions). For rotation of the test stimuli against the training stimuli we found transfer only for the normal PLW, but not for the PLWJ stimuli. Subjects were able to learn the completely arti- cial stimuli (group B) presented as PLWJ equally fast as the stimuli from group A. Conclusions: (1) New templates for movement recognition can be learned very quickly. (2) Learning aects at least two dierent levels of representation (local and holistic). (3) The learned holistic representations seem to be view-dependent. (4) There seems to be no signicant dierence in the learning process between stimuli derived from articial and natural movements.