From skeletons to bone graphs: Medial abstraction for object recognition

letons to Bone Graphs: Medial Abstraction for Object Recognition Diego Macrini University of Toronto Kaleem Siddiqi McGill University Sven Dickinson University of Toronto Medial descriptions, such as shock graphs, have gained significant momentum in the shape-based object recognition community due to their invariance to translation, rotation, scale and articulation and their ability to cope with moderate amounts of within-class deformation. While they attempt to decompose a shape into a set of parts, this decomposition can suffer from ligature-induced instability. In particular, the addition of even a small part can have a dramatic impact on the representation in the vicinity of its attachment. We present an algorithm for identifying and representing the ligature structure, and restoring the nonligature structures that remain. This leads to a bone graph, a new medial shape abstraction that captures a more intuitive notion of an object's parts than a skeleton or a shock graph, and...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Diego Macrini, Kaleem Siddiqi, Sven J. Dickinson
• Keywords: Bone Graphs, Computer Vision, CVPR 2008, Medial Shape Abstraction, Shape-based Object Recognition, Shock Graphs, View-based Object Recognition