SIG-011: International Workshop on Stochastic Image Grammars

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This travel grant supports two US participants to attend the International Workshop on Stochastic Image Grammars (SIG-11). The notion of stochastic image grammars encompasses hierarchical representations of objects and events occurring in images and video, and their associated learning and inference algorithms. The virtue of image grammars lies in their expressive power to represent an exponentially large number of object and event configurations by using a relatively much smaller vocabulary, and a few compositional rules. Statistics, machine learning, natural language processing, and cognitive psychology experience a resurgence of stochastic grammars. In computer vision, however, this momentum seems to be present only in the area of 2D object recognition. The main objective of the workshop is to promote interdisciplinary research among these traditionally separate scientific disciplines toward grammar-based formulations of a wider range of vision problems, beyond object recognition, such as, e.g., 3D structure from motion, and activity recognition. The workshop is also aimed at reducing the apparent disconnect between research groups working on image grammars, by addressing the need for a unified theoretical framework. To this end, SIG-11 provides a forum for sharing research experiences in grammars between the vision community and the keynote speakers who are experts in cognitive psychology, neuroscience, and natural language processing. Solicited peer-reviewed papers are expected to be published in the proceedings of the 13th International Conference on Computer Vision.