Martin Giese


will speak on

Representation of Biological Motion Based on Learned Prototypical Example Patterns

Learning-based methods have been applied successfully for the representation of the shape of stationary objects, like faces. The interpolation between learned two-dimensional prototypical views has provided a powerful techniques for applications in computer vision and computer graphics, like face recognition and the synthesis of artificial views of a face. Learning-based representations have also been shown to provide a consistent account for psychophysical and neurophysiological results on stationary object recognition. The work presented in this talk explores if similar concepts are also feasible for the representation of complex movement patterns and actions. The usefulness of learning-based representations of biological motion is demonstrated for two different fields of applications. A new computer vision method is presented that permits to approximate patterns of biological motion by interpolation between a small number of learned prototypical actions. It is shown that this method can be applied for the recognition of complex movement patterns and the style with which actions are performed. It is shown that the same theoretical approach permits also to synthesize artificial naturally-looking movements by “motion morphing”. The idea of a representation of biological movements based on learned prototypes seems also to provide a reasonable theoretical approach to account for action recognition in the visual system. A neural model is presented that is compatible with the known facts from neurophysiology, and which achieves a recognition of biological movement patterns, The model reproduces in particular the spatial and temporal invariance properties of biological motion recognition that have been demonstrated in psychophysical experiments. The model makes a number of specific predictions that can be tested in psychophysical and neurophysiological experiments.

The lecture will take place in the Lecture Hall, Room 203, 44 Cummington St.

on Monday, February 28, 2000
at 1:00 pm

Hosted by the Brain and Vision Research Laboratory