Fast radial symmetry for detecting points of interest
Top Cited Papers
- 4 August 2003
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 25 (8) , 959-973
- https://doi.org/10.1109/tpami.2003.1217601
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.Keywords
This publication has 18 references indexed in Scilit:
- A fast recursive algorithm for the computation of axial momentsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2001
- Algorithms for defining visual regions-of-interest: comparison with eye fixationsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2000
- Preprocessing of Face Images: Detection of Features and Pose NormalizationComputer Vision and Image Understanding, 1998
- Evaluating image processing algorithms that predict regions of interestPattern Recognition Letters, 1998
- Extracting facial features by an inhibitory mechanism based on gradient distributionsPattern Recognition, 1996
- Context-free attentional operators: The generalized symmetry transformInternational Journal of Computer Vision, 1995
- SYMMETRY CATCHES THE EYEPublished by Elsevier ,1987
- The Detection and Segmentation of Blobs in Infrared ImagesIEEE Transactions on Systems, Man, and Cybernetics, 1981
- Perceiving the centroid of curvilinearly bounded rolling shapesPerception & Psychophysics, 1980
- Use of the Hough transformation to detect lines and curves in picturesCommunications of the ACM, 1972