Paper
9 February 1989 Dense Depth Map Reconstruction Using Special Purpose Hardware
A. Distante, R. Mugnuolo, E. Stella, G. Attolico
Author Affiliations +
Proceedings Volume 1008, Expert Robots for Industrial Use; (1989) https://doi.org/10.1117/12.949136
Event: 1988 Cambridge Symposium on Advances in Intelligent Robotics Systems, 1988, Boston, MA, United States
Abstract
The advancements in machine vision technology have been substantial in recent years with the introduction of faster processors and the improvements in sensor technology. A depth map can be obtained with both direct and indirect methods. The first ones recover depth directly from ranging devices. The second ones recover 3-D information by means of shape from xxx and stereopsis. Our idea consists of integration of information from two different source: local shading analysis and stereo vision. At present this alternate method has been tested with satisfactory results on conventional hardware but it's impracticable for computing time. The use of advanced parallel hardware is surely suitable to achieve the real time response, but it is not justified for some application fields (where response time is not very critical) because of its cost. An alternate choice can fall on low-cost and simple architectures that allow a configuration to achieve the required speed/cost ratio for a particular vision application by using a combination of standard modules. In this paper our method for depth recover is analyzed in order to enhance the critical steps for computing time. They are expressed in terms of computation suitable for standard and special purpose modules.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Distante, R. Mugnuolo, E. Stella, and G. Attolico "Dense Depth Map Reconstruction Using Special Purpose Hardware", Proc. SPIE 1008, Expert Robots for Industrial Use, (9 February 1989); https://doi.org/10.1117/12.949136
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Image filtering

Robots

Image processing

Optical spheres

Error analysis

Image segmentation

Cameras

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