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Parallel Algorithms for Computer Vision.

Author: Tomaso Poggio; MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB.
Publisher: Ft. Belvoir : Defense Technical Information Center, APR 1990.
Edition/Format:   eBook : EnglishView all editions and formats
Database:WorldCat
Summary:
The main effort in this project has been directed towards the development of an integrated vision system, - the Vision Machine - based on a parallel supercomputer. The core of the Vision Machine is in fact a set of parallel algorithms for visual recognition and navigation in an unstructured environment. The present version of the Vision Machine has been demonstrated to process images in close to real time by (1)  Read more...
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Material Type: Internet resource
Document Type: Internet Resource
All Authors / Contributors: Tomaso Poggio; MASSACHUSETTS INST OF TECH CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB.
OCLC Number: 227757487
Notes: Final rept. 31 Aug 1988-31 Jan 1990.
Description: 66 p. ; 23 x 29 cm.

Abstract:

The main effort in this project has been directed towards the development of an integrated vision system, - the Vision Machine - based on a parallel supercomputer. The core of the Vision Machine is in fact a set of parallel algorithms for visual recognition and navigation in an unstructured environment. The present version of the Vision Machine has been demonstrated to process images in close to real time by (1) computing first several low-level cues, such as edges, stereo disparity, optical flow, color and texture, (2) integrating them to extract a cartoon-like description of the scene in terms of the physical discontinuities of surfaces, and (3) using this cartoon in a recognition stage, based on parallel model matching. In addition to the development of the parallel algorithms, their implementation and testing, we have also done substantial work in several areas that are very closely related. These include (1) design and fabrication of VLSI circuits to transfer to potentially cheap and fast hardware some of the software algorithms, (2) initial development of techniques to synthesize by learning vision algorithms, and (3) several projects involving autonomous navigation of small robots.

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