Parallel Algorithms for Computer Vision on the Connection Machine
The Connection Machine is a fine-grained parallel computer having up to 64K processors. It supports both local communication among the processors, which are situated in a two-dimensional mesh, and high-bandwidth communication among processors at arbitrary locations, using a message-passing ne...
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Language: | en_US |
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2004
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Online Access: | http://hdl.handle.net/1721.1/5597 |
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author | Little, James J. |
author_facet | Little, James J. |
author_sort | Little, James J. |
collection | MIT |
description | The Connection Machine is a fine-grained parallel computer having up to 64K processors. It supports both local communication among the processors, which are situated in a two-dimensional mesh, and high-bandwidth communication among processors at arbitrary locations, using a message-passing network. We present solutions to a set of Image Understanding problems for the Connection Machine. These problems were proposed by DARPA to evaluate architectures for Image Understanding systems, and are intended to comprise a representative sample of fundamental procedures to be used in Image Understanding. The solutions on the Connection Machine embody general methods for filtering images, determining connectivity among image elements, determining spatial relations of image elements, and computing graph properties, such as matchings and shortest paths. |
first_indexed | 2024-09-23T09:49:30Z |
id | mit-1721.1/5597 |
institution | Massachusetts Institute of Technology |
language | en_US |
last_indexed | 2024-09-23T09:49:30Z |
publishDate | 2004 |
record_format | dspace |
spelling | mit-1721.1/55972019-04-12T13:39:34Z Parallel Algorithms for Computer Vision on the Connection Machine Little, James J. The Connection Machine is a fine-grained parallel computer having up to 64K processors. It supports both local communication among the processors, which are situated in a two-dimensional mesh, and high-bandwidth communication among processors at arbitrary locations, using a message-passing network. We present solutions to a set of Image Understanding problems for the Connection Machine. These problems were proposed by DARPA to evaluate architectures for Image Understanding systems, and are intended to comprise a representative sample of fundamental procedures to be used in Image Understanding. The solutions on the Connection Machine embody general methods for filtering images, determining connectivity among image elements, determining spatial relations of image elements, and computing graph properties, such as matchings and shortest paths. 2004-10-01T20:10:31Z 2004-10-01T20:10:31Z 1986-11-01 AIM-928 http://hdl.handle.net/1721.1/5597 en_US AIM-928 31 p. 4037682 bytes 1518931 bytes application/postscript application/pdf application/postscript application/pdf |
spellingShingle | Little, James J. Parallel Algorithms for Computer Vision on the Connection Machine |
title | Parallel Algorithms for Computer Vision on the Connection Machine |
title_full | Parallel Algorithms for Computer Vision on the Connection Machine |
title_fullStr | Parallel Algorithms for Computer Vision on the Connection Machine |
title_full_unstemmed | Parallel Algorithms for Computer Vision on the Connection Machine |
title_short | Parallel Algorithms for Computer Vision on the Connection Machine |
title_sort | parallel algorithms for computer vision on the connection machine |
url | http://hdl.handle.net/1721.1/5597 |
work_keys_str_mv | AT littlejamesj parallelalgorithmsforcomputervisionontheconnectionmachine |