The Representation and Matching of Pictorial Structures
Abstract
The primary problem dealt with in this paper is the following. Given some description of a visual object, find that object in an actual photograph. Part of the solution to this problem is the specification of a descriptive scheme, and a metric on which to base the decision of "goodness" of matching or detection.
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Early research on object recognition was based on template matching techniques and simple part-based models, focusing on specific objects whose spatial layouts are roughly rigid, such as faces.
“Early research on object recognition was based on template matching techniques and simple part-based models (Fischler and Elschlager 1973), focusing on specific objects whose spatial layouts are roughly rigid, such as faces.”
From Deep Learning for Generic Object Detection: A Survey (2020) · cites this paper as Fischler and Elschlager 1973
Cites
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- Authors
- Fischler, M. A., & Elschlager, R. A.
- Affiliations
- Lockheed Missiles and Space Company (United States) (US)
- Venue
- IEEE Transactions on Computers
- Published
- 1973-01
- Volume
- C-22
- Issue
- 1
- Pages
- 67-92
- ISSN
- 0018-9340 (ISSN-L)
- 1557-9956
- 2326-3814
- OpenAlex
- W2045798786
- Cited by
- 1,322
- References
- 13
- Citations by year
- 2026: 9 · 2025: 24 · 2024: 34 · 2023: 24 · 2022: 34 · 2021: 45 · 2020: 47 · 2019: 53 · 2018: 52 · 2017: 56 · 2016: 78 · 2015: 84 · 2014: 94 · 2013: 77 · 2012: 54
- FWCI
- 11.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Computers (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Keywords
- object matching, image retrieval
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