The representation and matching of categorical shape

We present a framework for categorical shape recognition. The coarse shape of an object is captured by a multiscale blob decomposition, representing the compact and elongated parts of an object at appropriate scales. These parts, in turn, map to nodes in a directed acyclic graph, in which edges encode both semantic relations (parent/child) as well as geometric relations. Given two image descriptions, each represented as a directed acyclic graph, we draw on spectral graph theory to derive a new algorithm for computing node correspondence in the presence of noise and occlusion. In computing correspondence, the similarity of two nodes is a function of their topological (graph) contexts, their geometric (relational) contexts, and their node contents. We demonstrate the approach on the domain of viewbased 3-D object recognition.

• Type: Journal
• Year: 2006
• Where: CVIU
• Authors: Ali Shokoufandeh, Lars Bretzner, Diego Macrini, M. Fatih Demirci, Clas Jönsson, Sven J. Dickinson
• Keywords: Categorical Shape Recognition, CVIU 2006, Directed Acyclic Graph, Multiscale Blob Decomposition