The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Fast radial symmetry for detecting points of interest
Abstract
A new transform is presented that utilizes local radial symmetry to highlight points of interest within a scene. Its low-computational complexity and fast runtimes makes this method well-suited for real-time vision applications. The performance of the transform is demonstrated on a wide variety of images and compared with leading techniques from the literature. Both as a facial feature detector and as a generic region of interest detector the new transform is seen to offer equal or superior performance to contemporary techniques at a relatively low-computational cost. A real-time implementation of the transform is presented running at over 60 frames per second on a standard Pentium III PC.
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Cites
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Image Features From Phase Congruency
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Algorithms for defining visual regions-of-interest: comparison with eye fixations
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Context-free attentional operators: The generalized symmetry transform
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Symmetry and Asymmetry from Local Phase
Kovesi, P. D. (1997) · UWA Profiles and Research Repository (University of Western Australia) · Cited by 273
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A Fast Radial Symmetry Transform for Detecting Points of Interest
Loy, G., & Zelinsky, A. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47969-4_24 · Cited by 98
Self-citation“Center-of-gravity” Tendencies for fixations and flow patterns
Richards, W., & Kaufman, L. (1969) · Perception & Psychophysics · doi:10.3758/bf03210526 · Cited by 73
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Self-citationIn situ genotyping of a pooled strain library after characterizing complex phenotypes
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Metadata
- Authors
- Loy, G., & Zelinsky, A.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2003-08
- Volume
- 25
- Issue
- 8
- Pages
- 959-973
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2109722393
- Cited by
- 593
- References
- 13
- FWCI
- 20.03
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
