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Abstract: INTRODUCTION Young disciplines often experience moments of doubt: "Are we doing the right thing?" or "Is this approach viable?" [1]. Nowhere is this better exemplified than in the study of computer vision [2]. While progress has been made, the goal of general vision, on the order of human visual perception, remains elusive. Recently, this has led * Please address all correspondence to Michael J. Tarr, P.O. Box 208205, New Haven, CT 06520-8205, E-mail address: tarr@cs.yale.edu to the suggestion... (Update)
Context of citations to this paper: More
.... on representations, provides the best hope for modeling and understanding general purpose vision in humans and machines [Tarr and Black, 1991] . While recognizing that the purposive paradigm may be appropriate for describing low level, or reflexive, behaviors they...
.... focus feature #0 Thus in conclusion, if one of the holy grails of vision science is the development of the general vision system [13, 14], our particular version of the search is for a system architecture in which generality is provided by a Bayesian network (or equivalent...
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BibTeX entry: (Update)
Tarr, M.J., Black, M.J., A Computational and Evolutionary Perspective on the Role of Representation in Vision, CVGIP(60), No. 1, July 1994, pp. 65-73. http://citeseer.ist.psu.edu/tarr94computational.html More
@article{ tarr94computational,
author = "Michael J. Tarr and Michael J. Black",
title = "A Computational and Evolutionary Perspective on the Role of Representation in Vision",
journal = "Computer Vision, Graphics, and Image Processing. Image Understanding",
volume = "60",
number = "1",
pages = "65--73",
year = "1994",
url = "citeseer.ist.psu.edu/tarr94computational.html" }
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