Paper
19 February 1988 Rapid Recognition Out Of A Large Model Base Using Prediction Hierarchies And Machine Parallelism
J.Brian Burns, Leslie J. Kitchen
Author Affiliations +
Proceedings Volume 0848, Intelligent Robots and Computer Vision VI; (1988) https://doi.org/10.1117/12.942740
Event: Advances in Intelligent Robotics Systems, 1987, Cambridge, CA, United States
Abstract
An object recognition system is presented to handle the computational complexity posed by a large model base, an unconstrained viewpoint, and the structural complexity and detail inherent in the projection of an object. The design is based on two ideas. The first is to compute descriptions of what the objects should look like in the im-age, called predictions, before the recognition task begins. This reduces actual recognition to a 2D matching process, speeding up recognition time for 3D objects. The second is to represent all the predictions by a single, combined IS-A and PART-OF hierarchy called a prediction hierarchy. The nodes in this hierarchy are partial descriptions that are common to views and hence constitute shared processing subgoals during matching. The recognition time and storage demands of large model bases and complex models are substantially reduced by subgoal sharing: projections with similarities explicitly share the recognition and representation of their common aspects. A prototype system for the automatic compilation of a prediction hierarchy from a 3D model base is demonstrated using a set of polyhedral objects and projections from an unconstrained range of viewpoints. In addition, the adaptation of prediction hierarchies for use on the UMass Image Understanding Architecture is considered. Object recognition using prediction hierar-chies can naturally exploit the hierarchical parallelism of this machine.
© (1988) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
J.Brian Burns and Leslie J. Kitchen "Rapid Recognition Out Of A Large Model Base Using Prediction Hierarchies And Machine Parallelism", Proc. SPIE 0848, Intelligent Robots and Computer Vision VI, (19 February 1988); https://doi.org/10.1117/12.942740
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image segmentation

3D modeling

Object recognition

Image understanding

Computer vision technology

Image processing

Machine vision

RELATED CONTENT

Qualitative three-dimensional shape from stereo
Proceedings of SPIE (February 01 1991)
Finding distinctive colored regions in images
Proceedings of SPIE (February 01 1991)
Cylindrical Part Recognition In Occluding Contours
Proceedings of SPIE (March 01 1990)
Occlusion-free next view planning
Proceedings of SPIE (August 06 1993)
Knowledge-based system for analysis of aerial images
Proceedings of SPIE (February 01 1991)
Rule-Based Evidence Accrual System For Image Understanding
Proceedings of SPIE (January 17 1985)

Back to Top