The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Model-Based Recognition and Localization from Sparse Range or Tactile Data
Open accessAbstract
This paper discusses how local measurements of three- dimensional positions and surface normals ( recorded by a set of tactile sensors, or by three-dimensional range sensors), may be used to identify and locate objects from among a set of known objects. The objects are modeled as polyhedra having up to six degrees of freedom relative to the sensors. We show that inconsistent hypotheses about pairings between sensed points and object surfaces can be discarded efficiently by using local constraints on distances between faces, angles between face normals, and angles (relative to the surface normals) of vectors between sensed points. We show by simu lation and by mathematical bounds that the number of hy potheses consistent with these constraints is small. We also show how to recover the position and orientation of the object from the sensory data. The algorithm's performance on data obtained from a triangulation range sensor is illustrated.
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Cites
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Spatial Planning: A Configuration Space Approach
Lozano-Perez (1983) · IEEE Transactions on Computers · doi:10.1109/tc.1983.1676196 · Cited by 2,113
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Woodham, R. J. (1980) · Optical Engineering · doi:10.1117/12.7972479 · Cited by 2,003
Mathematical Handbook for Scientists and Engineers
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A Perspective on Range Finding Techniques for Computer Vision
Jarvis, R. A. (1983) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1983.4767365 · Cited by 782
Description and recognition of curved objects☆
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From Images to Surfaces: A Computational Study of the Human Early Visual System
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Self-citationDepth from edge and intensity based stereo
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Psychophysical and computational studies towards a theory of human stereopsis
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Recognising and Locating Partially Visible Objects: The Local-Feature-Focus Method
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Cited by
Example-based learning for view-based human face detection
Sung, K.-K., & Poggio, T. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.655648 · Cited by 1,773
Fitting parameterized three-dimensional models to images
Lowe, D. G. (1991) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.134043 · Cited by 837
Model-based recognition in robot vision
Chin, R. T., & Dyer, C. R. (1986) · ACM Computing Surveys · doi:10.1145/6462.6464 · Cited by 567
Error modeling in stereo navigation
Matthies, L., & Shafer, S. (1987) · IEEE Journal on Robotics and Automation · doi:10.1109/jra.1987.1087097 · Cited by 509
50 Years of object recognition: Directions forward
Andreopoulos, A., & Tsotsos, J. K. (2013) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2013.04.005 · Cited by 347
Metadata
- Authors
- Grimson, W. E. L., & Lozano-Pérez, T.
- Venue
- The International Journal of Robotics Research
- Publisher
- SAGE Publications
- Published
- 1984-09
- Volume
- 3
- Issue
- 3
- Pages
- 3-35
- ISSN
- 0278-3649 (ISSN-L)
- 1741-3176
- OpenAlex
- W1532977286
- Cited by
- 586
- References
- 26
- FWCI
- 52.96
- Type
- journal article
- Language
- en
- Open access
- green
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- Grimson, W. E. L., & Lozano-Pérez, T. (1984). Model-Based Recognition and Localization from Sparse Range or Tactile Data. The International Journal of Robotics Research. https://doi.org/10.1177/027836498400300301
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
