DocumentCode :
1289306
Title :
Automatic generation of object recognition programs
Author :
Ikeuchi, Katsushi ; Kanade, Takeo
Author_Institution :
Dept. of Robotics Inst. & Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
76
Issue :
8
fYear :
1988
fDate :
8/1/1988 12:00:00 AM
Firstpage :
1016
Lastpage :
1035
Abstract :
Issues and techniques are discussed to automatically compile object and sensor models into a visual recognition strategy for recognizing and locating an object in three-dimensional space from visual data. Automatic generation of recognition programs by compilation, in an attempt to automate this process, is described. An object model describes geometric and photometric properties of an object to be recognized. A sensor model specifies the sensor characteristics in predicting object appearances and variations of feature values. It is emphasized that the sensors, as well as objects, must be explicitly modeled to achieve the goal of automatic generation of reliable and efficient recognition programs. Actual creation of interpretation trees for two objects and their execution for recognition from a bin of parts are demonstrated
Keywords :
computer vision; pattern recognition; automatic generation of programs; compilation; computer vision; interpretation trees; object location; object model; object models; object recognition programs; photometric properties; predicting object appearances; recognition from bin of parts; sensor characteristics; sensor models; techniques; three-dimensional space; visual data; visual recognition strategy; Classification tree analysis; Data mining; Handwriting recognition; Machine vision; Object oriented modeling; Object recognition; Photometry; Predictive models; Sensor phenomena and characterization; Shape; Solid modeling; Target recognition;
fLanguage :
English
Journal_Title :
Proceedings of the IEEE
Publisher :
ieee
ISSN :
0018-9219
Type :
jour
DOI :
10.1109/5.5972
Filename :
5972
Link To Document :
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