SRL2004: Statistical Relational Learning and
its Connections to Other Fields

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Pictorial Structure Models for Visual Recognition

Dan Huttenlocher
Cornell University

There has been considerable recent work in object recognition on representations that combine both local visual appearance and global spatial constraints. Several such approaches are based on statistical characterizations of the spatial relations between local image patches. In this talk I will give an overview of one such approach, called pictorial structures, which uses spatial relations between pairs of parts. I will focus on the recent development of highly efficient techniques both for learning certain forms of pictorial structure models from examples and for detecting objects using these models.