Help Privacy Policy Disclaimer
  Advanced SearchBrowse




Journal Article

Learning to discriminate complex movements: Biological versus artificial trajectories


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

External Resource
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available

Jastorff, J., Kourtzi, Z., & Giese, M. (2006). Learning to discriminate complex movements: Biological versus artificial trajectories. Journal of Vision, 6(3), 791-804. doi:10.1167/6.8.3.

Cite as: https://hdl.handle.net/21.11116/0000-0004-83A5-D
The recognition of complex body movements and actions is a fundamental visual capacity very important for social communication. It seems possible that movement recognition is based on a general capability of the visual system to learn complex visual motion patterns. Alternatively, this visual function might exploit specialized mechanisms for the analysis of biologically relevant movements, for example, of humans or animals. To investigate this question, we trained human observers to discriminate novel motion patterns that were generated, exploiting a new technique for stimulus generation by motion morphing. We tested the learning of different classes of novel movement stimuli. One group of stimuli was fully consistent with human movements. A second class of stimuli was based on artificial skeleton models that were inconsistent with human and animal bodies. A third group of stimuli specified the same local motion information as human movements but was inconsistent with an underlying articulated shape. Participants learned both classes of articulated movements very fast in an orientation-dependent manner. Learning speed and accuracy were strikingly similar and independent of the similarity of the stimuli with biologically relevant body shapes. For the class of stimuli without underlying articulated shape, however, we did not observe significant improvements of the discrimination performance after training. Our results indicate the existence of a fast visual learning process for complex articulated movement patterns, which likely is relevant for biological motion perception. This process seems to operate independently of the consistency of the patterns with biologically relevant body shapes but seems to require the compatibility of the learned movements with a global underlying shape.