Title :
A framework for shape representation and recognition
Author :
Zhu, Song Chun ; Yuille, A.L.
Author_Institution :
Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA
Abstract :
Describes a novel framework which represents and recognizes animate objects from their silhouettes. The authors model animate objects at three levels of complexity: (i) primitives, (ii) mid-grained shapes, which are deformations of the primitives, and (iii) objects constructed by using a grammar to join mid-grained shapes together. The deformations of the primitives can be characterized by principal component analysis. This framework provides a generic low dimensional parameterized representation for animate objects and it also gives a formalism for solving the inverse problem of object recognition. The paper is mainly focused on generating and representing animate objects. The authors briefly describe how this representation can be automatically extracted for recognition, the complete system is described in Zhu and Yuille (1994)
Keywords :
image recognition; image representation; inverse problems; object recognition; animate objects; deformations; generic low dimensional parameterized representation; grammar; inverse problem; mid-grained shapes; object recognition; primitives; principal component analysis; recognition; shape representation; silhouettes; Animation; Bones; Deformable models; Fasteners; Joints; Marine animals; Shape; Skeleton; Tail; Torso;
Conference_Titel :
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location :
Austin, TX
Print_ISBN :
0-8186-6952-7
DOI :
10.1109/ICIP.1994.413399