A Primitive Recognizer of Figures in a Scene

Given a scene, as seen for instance from a T.V. camera or a picture, it is desired to analyze it to organize, differentiate and identify desired objects or classes of objects (i.e., patterns) in it. The present report describes a program, written in CONVERT, which partially achieves this goal....

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Main Author: Guzman, Adolfo
Language:en_US
Published: 2004
Online Access:http://hdl.handle.net/1721.1/5876
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author Guzman, Adolfo
author_facet Guzman, Adolfo
author_sort Guzman, Adolfo
collection MIT
description Given a scene, as seen for instance from a T.V. camera or a picture, it is desired to analyze it to organize, differentiate and identify desired objects or classes of objects (i.e., patterns) in it. The present report describes a program, written in CONVERT, which partially achieves this goal. Two inputs to the program determine its behavior and response: 1. The scene to be analyzed, which is entered in a symbolic format (it may contain 3-dimensional and curved objects). 2. A symbolic description -- called the model -- of the class for the objects we want to identify in the scene (1): Given a set of models for the objects we want to locate, and a scene or picture, the program will identify in it all those objects or figures which are similar to one of the models, provided they appear complete in the picture (i.e., no partial occlusion or hidden parts). Recognition is independent of position, orientation, size etc.; it strongly depends on the topology of the model. Important restrictions and suppositions are: (a) the input is assumed perfect --noiseless-- and highly organized; (b) more than one mode is, in general, required for the description of one object and (c) only objects which appear unobstructed are recognized. Work is continuing in order to drop restriction (c) and to improve (a).
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spelling mit-1721.1/58762019-04-11T04:47:04Z A Primitive Recognizer of Figures in a Scene Guzman, Adolfo Given a scene, as seen for instance from a T.V. camera or a picture, it is desired to analyze it to organize, differentiate and identify desired objects or classes of objects (i.e., patterns) in it. The present report describes a program, written in CONVERT, which partially achieves this goal. Two inputs to the program determine its behavior and response: 1. The scene to be analyzed, which is entered in a symbolic format (it may contain 3-dimensional and curved objects). 2. A symbolic description -- called the model -- of the class for the objects we want to identify in the scene (1): Given a set of models for the objects we want to locate, and a scene or picture, the program will identify in it all those objects or figures which are similar to one of the models, provided they appear complete in the picture (i.e., no partial occlusion or hidden parts). Recognition is independent of position, orientation, size etc.; it strongly depends on the topology of the model. Important restrictions and suppositions are: (a) the input is assumed perfect --noiseless-- and highly organized; (b) more than one mode is, in general, required for the description of one object and (c) only objects which appear unobstructed are recognized. Work is continuing in order to drop restriction (c) and to improve (a). 2004-10-01T20:50:28Z 2004-10-01T20:50:28Z 1967-01-01 AIM-119 http://hdl.handle.net/1721.1/5876 en_US AIM-119 32 p. 23033760 bytes 660424 bytes application/postscript application/pdf application/postscript application/pdf
spellingShingle Guzman, Adolfo
A Primitive Recognizer of Figures in a Scene
title A Primitive Recognizer of Figures in a Scene
title_full A Primitive Recognizer of Figures in a Scene
title_fullStr A Primitive Recognizer of Figures in a Scene
title_full_unstemmed A Primitive Recognizer of Figures in a Scene
title_short A Primitive Recognizer of Figures in a Scene
title_sort primitive recognizer of figures in a scene
url http://hdl.handle.net/1721.1/5876
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