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Cited by 492

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HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects

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Ayache, Nicholas, Faugeras, Olivier D.·1986·IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI 10.1109/tpami.1986.4767751
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Abstract

A new method has been designed to identify and locate objects lying on a flat surface. The merit of the approach is to provide strong robustness to partial occlusions (due for instance to uneven lighting conditions, shadows, highlights, touching and overlapping objects) thanks to a local and compact description of the objects boundaries and to a new fast recognition method involving generation and recursive evaluation of hypotheses named HYPER (HY potheses Predicted and Evaluated Recursively). The method has been integrated within a vision system coupled to an indutrial robot arm, to provide automatic picking and repositioning of partially overlapping industrial parts.

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Metadata

Authors
Ayache, N., & Faugeras, O. D.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
1986-01
Volume
PAMI-8
Issue
1
Pages
44-54
ISSN
0162-8828 (ISSN-L)
DOI
10.1109/tpami.1986.4767751
OpenAlex
W2000048778
Cited by
492
References
0
FWCI
26.98
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects. https://app.cochat.ai/papers/10.1109/tpami.1986.4767751
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Ayache, N., & Faugeras, O. D. (1986). HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.1986.4767751

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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.