DocumentCode
299864
Title
Object recognition and localization from scanning beam sensors
Author
Wallack, Aaron S. ; Canny, John F.
Author_Institution
Comput. Sci. Div., California Univ., Berkeley, CA, USA
Volume
1
fYear
1995
fDate
21-27 May 1995
Firstpage
247
Abstract
Model based object recognition and object localization are fundamental problems in industrial automation. The authors present techniques which use a scanner composed of binary light beam sensors to quickly recognize objects (as fast as 5 microseconds) and to accurately localize objects (0.025 millimeters), and they describe localization and recognition experiments and present results. Binary sensors only sense whether the part is present or absent at a particular location, and their high performance is due to their simple specification. Fast recognition is achieved by using indexing to solve the correspondence problem, the problem of interpreting the sensed data as model features; indexing involves using the sensed data to directly look up the correspondence information using a precomputed indexing table. Since each experiment only produces a single indexing vector, indexing tables need to be complete; in this paper the authors detail a complete indexing construction method for flat polygonal and polyhedral objects
Keywords
computer vision; image sensors; object recognition; binary light beam sensors; binary sensors; correspondence problem; flat polygonal objects; industrial automation; model features; object localization; object recognition; polyhedral objects; precomputed indexing table; scanning beam sensor; Computer industry; Computer science; Construction industry; Heart; Indexing; Machine vision; Object recognition; Robotics and automation; Sensor phenomena and characterization; Structural beams;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on
Conference_Location
Nagoya
ISSN
1050-4729
Print_ISBN
0-7803-1965-6
Type
conf
DOI
10.1109/ROBOT.1995.525293
Filename
525293
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