Object Recognition in the Geometric Era: A Retrospective
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Before 1990 the leading paradigm of object recognition was based on geometric representations, with focus later moving away from geometry and prior models towards statistical classifiers based on appearance features.
“Before 1990 the leading paradigm of object recognition was based on geometric representations (Mundy 2006;Ponce et al. 2007), with the focus later moving away from geometry and prior models towards the use of statistical classifiers [such as Neural Networks (Rowley et al. 1998), SVM (Osuna et al. 1997) and Adaboost (Viola and Jones 2001;Xiao et al. 2003)] based on appearance features (Murase and N”
From Deep Learning for Generic Object Detection: A Survey (2020) · cites this paper as Mundy 2006
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- Authors
- Mundy, J. L.
- Affiliations
- Brown University (US)
- Corresponding author
- Mundy, Joseph L.
- ORCID
- Mundy, Joseph L.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2006
- Pages
- 3-28
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1910706092
- Cited by
- 100
- References
- 92
- Citations by year
- 2024: 1 · 2023: 2 · 2022: 2 · 2021: 9 · 2020: 2 · 2019: 7 · 2018: 6 · 2017: 3 · 2016: 7 · 2015: 16 · 2014: 8 · 2013: 13 · 2012: 6
- FWCI
- 1.70
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (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 recognition, perspective invariance, intensity features, statistical learning, appearance-based recognition, history of computer vision
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