Accession Number : ADA295737
Title : View-Based Strategies for 3D Object Recognition.
Descriptive Note : Memorandum rept.,
Corporate Author : MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB
Personal Author(s) : Sinha, Pawan ; Poggio, Tomaso
PDF Url : ADA295737
Report Date : NOV 1994
Pagination or Media Count : 7
Abstract : A persistent issue of debate in the area of 3D object recognition concerns the nature of the experimentally acquired object models in the primate visual system. One prominent proposal in this regard has expounded the use of object centered models, such as representations of the objects' 3D structures in a coordinate frame independent of the viewing parameters Marr and Nishihara, 1978. In contrast to this is another proposal which suggests that the viewing parameters encountered during the learning phase might be inextricably linked to subsequent performance on a recognition task Tarr and Pinker, 1989; Poggio and Edelman, 1990. The 'object model', according to this idea, is simply a collection of the sample views encountered during training. Given that object centered recognition strategies have the attractive feature of leading to viewpoint independence, they have garnered much of the research effort in the field of computational vision. Furthermore, since human recognition performance seems remarkably robust in the face of imaging variations Ellis et at., 1989, it has often been implicitly assumed that the visual system employs an object centered strategy. In the present study we examine this assumption more closely. Our experimental results with a class of novel 3D structures strongly suggest the use of a view-based strategy by the human visual system even when it has the opportunity of constructing and using object-centered models. In fact, for our chosen class of objects, the results seem to support a stronger claim: 3D object recognition is 2D view-based.
Descriptors : *RECOGNITION, *VISUAL PERCEPTION, *PRIMATES, *NEUROPHYSIOLOGY, COMPUTATIONS, STRATEGY, MODELS, PERFORMANCE(HUMAN), HUMANS, PARAMETERS, COORDINATES, FRAMES, VISION, LEARNING, VIEWERS.
Subject Categories : Anatomy and Physiology
Distribution Statement : APPROVED FOR PUBLIC RELEASE