Spatiotemporal Contour Grouping Using Abstract Part Models [chapter]

Pablo Sala, Diego Macrini, Sven Dickinson
2011 Lecture Notes in Computer Science  
In recent work [1], we introduced a framework for modelbased perceptual grouping and shape abstraction using a vocabulary of simple part shapes. Given a user-defined vocabulary of simple abstract parts, the framework grouped image contours whose abstract shape was consistent with one of the part models. While the results showed promise, the representational gap between the actual image contours that make up an exemplar shape and the contours that make up an abstract part model is significant,
more » ... d an abstraction of a group of image contours may be consistent with more than one part model; therefore, while recall of ground-truth parts was good, precision was poor. In this paper, we address the precision problem by moving the camera and exploiting spatiotemporal constraints in the grouping process. We introduce a novel probabilistic, graph-theoretic formulation of the problem, in which the spatiotemporal consistency of a perceptual group under camera motion is learned from a set of training sequences. In a set of comprehensive experiments, we demonstrate (not surprisingly) how a spatiotemporal framework for part-based perceptual grouping significantly outperforms a static image version.
doi:10.1007/978-3-642-19282-1_43 fatcat:cl5l52q6pfeo7kxl3dwiyjnxfi