Journal ArticleDOI
Fast radial symmetry for detecting points of interest
G. Loy,Alexander Zelinsky +1 more
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TLDR
A new transform is presented that utilizes local radial symmetry to highlight points of interest within a scene and is seen to offer equal or superior performance to contemporary techniques at a relatively low-computational cost.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.read more
Citations
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Proceedings ArticleDOI
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References
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Journal ArticleDOI
Use of the Hough transformation to detect lines and curves in pictures
Richard O. Duda,Peter E. Hart +1 more
TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.
Image Features From Phase Congruency
TL;DR: Videre: Journal of Computer Vision Research is a quarterly journal published electronically on the Internet by The MIT Press, Cambridge, Massachusetts, 02142 and prices subject to change without notice.
Journal ArticleDOI
Finding circles by an array of accumulators
TL;DR: This procedure is an extension and improvement of the circle-finding concept sketched by Duda and Hart as an extension of the Hough straight-line finder.
Journal ArticleDOI
Algorithms for defining visual regions-of-interest: comparison with eye fixations
C.M. Privitera,L.W. Stark +1 more
TL;DR: This paper investigates and develops a methodology that serves to automatically identify a subset of aROIs (algorithmically detected ROIs) using different image processing algorithms (IPAs), and appropriate clustering procedures, and compares hROIs with hROI as a criterion for evaluating and selecting bottom-up, context-free algorithms.
Journal ArticleDOI
Context-free attentional operators: the generalized symmetry transform
TL;DR: An attention operator based on the intuitive notion of symmetry, which generalized many of the existing methods of detecting regions of interest is presented, a low-level operator that can be applied successfully without a priori knowledge of the world.