Fast radial symmetry for detecting points of interest

doi:10.1109/TPAMI.2003.1217601

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Fast radial symmetry for detecting points of interest

Journal Article•DOI•

Fast radial symmetry for detecting points of interest

G. Loy¹, Alexander Zelinsky¹•Institutions (1)

01 Aug 2003-IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE Computer Society)-Vol. 25, Iss: 8, pp 959-973

TL;DR: 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.

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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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Journal Article•DOI•

In the Eye of the Beholder: A Survey of Models for Eyes and Gaze

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Dan Witzner Hansen¹, Qiang Ji²•Institutions (2)

IT University of Copenhagen¹, Rensselaer Polytechnic Institute²

01 Mar 2010-IEEE Transactions on Pattern Analysis and Machine Intelligence

TL;DR: This review shows that, despite their apparent simplicity, the development of a general eye detection technique involves addressing many challenges, requires further theoretical developments, and is consequently of interest to many other domains problems in computer vision and beyond.

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Abstract: Despite active research and significant progress in the last 30 years, eye detection and tracking remains challenging due to the individuality of eyes, occlusion, variability in scale, location, and light conditions. Data on eye location and details of eye movements have numerous applications and are essential in face detection, biometric identification, and particular human-computer interaction tasks. This paper reviews current progress and state of the art in video-based eye detection and tracking in order to identify promising techniques as well as issues to be further addressed. We present a detailed review of recent eye models and techniques for eye detection and tracking. We also survey methods for gaze estimation and compare them based on their geometric properties and reported accuracies. This review shows that, despite their apparent simplicity, the development of a general eye detection technique involves addressing many challenges, requires further theoretical developments, and is consequently of interest to many other domains problems in computer vision and beyond.

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1,514 citations

Cites methods from "Fast radial symmetry for detecting ..."

...A study on the comparative complexity of symmetry operators was conducted by Loy and Zelinsky [93]....
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...Rather than determining the contribution each pixel makes to the symmetry of pixels in its neighborhood, Loy and Zelinsky [93] propose the Fast Radial Symmetry Transform by considering the contribution of a local neighborhood to a central pixel....
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...Matsumoto and Zelinsky [98] use 2D image templates to represent facial features located on a 3D facial model....
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Book•

Local Invariant Feature Detectors: A Survey

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Tinne Tuytelaars¹, Krystian Mikolajczyk²•Institutions (2)

Katholieke Universiteit Leuven¹, University of Surrey²

16 Jun 2008

TL;DR: An overview of invariant interest point detectors can be found in this paper, where an overview of the literature over the past four decades organized in different categories of feature extraction methods is presented.

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Abstract: In this survey, we give an overview of invariant interest point detectors, how they evolvd over time, how they work, and what their respective strengths and weaknesses are. We begin with defining the properties of the ideal local feature detector. This is followed by an overview of the literature over the past four decades organized in different categories of feature extraction methods. We then provide a more detailed analysis of a selection of methods which had a particularly significant impact on the research field. We conclude with a summary and promising future research directions.

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1,144 citations

Journal Article•DOI•

Vision-Based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems: Perspectives and Survey

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Andreas Mogelmose¹, Mohan M. Trivedi², Thomas B. Moeslund¹•Institutions (2)

Aalborg University¹, University of California, San Diego²

01 Dec 2012-IEEE Transactions on Intelligent Transportation Systems

TL;DR: A survey of the traffic sign detection literature, detailing detection systems for traffic sign recognition (TSR) for driver assistance and discussing future directions of TSR research, including the integration of context and localization.

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Abstract: In this paper, we provide a survey of the traffic sign detection literature, detailing detection systems for traffic sign recognition (TSR) for driver assistance. We separately describe the contributions of recent works to the various stages inherent in traffic sign detection: segmentation, feature extraction, and final sign detection. While TSR is a well-established research area, we highlight open research issues in the literature, including a dearth of use of publicly available image databases and the over-representation of European traffic signs. Furthermore, we discuss future directions of TSR research, including the integration of context and localization. We also introduce a new public database containing U.S. traffic signs.

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620 citations

Cites methods from "Fast radial symmetry for detecting ..."

...HOG is also used by Creusen et al. [65], but they augment the HOG feature vectors with color information to make them even more robust....
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Journal Article•DOI•

Methods for Nuclei Detection, Segmentation, and Classification in Digital Histopathology: A Review—Current Status and Future Potential

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Humayun Irshad, Antoine Veillard, Ludovic Roux, Daniel Racoceanu

01 Jan 2014-IEEE Reviews in Biomedical Engineering

TL;DR: This study presents, discusses, and extracts the major trends from an exhaustive overview of various nuclei detection, segmentation, feature computation, and classification techniques used in histopathology imagery, specifically in hematoxylin-eosin and immunohistochemical staining protocols.

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Abstract: Digital pathology represents one of the major evolutions in modern medicine. Pathological examinations constitute the gold standard in many medical protocols, and also play a critical and legal role in the diagnosis process. In the conventional cancer diagnosis, pathologists analyze biopsies to make diagnostic and prognostic assessments, mainly based on the cell morphology and architecture distribution. Recently, computerized methods have been rapidly evolving in the area of digital pathology, with growing applications related to nuclei detection, segmentation, and classification. In cancer research, these approaches have played, and will continue to play a key (often bottleneck) role in minimizing human intervention, consolidating pertinent second opinions, and providing traceable clinical information. Pathological studies have been conducted for numerous cancer detection and grading applications, including brain, breast, cervix, lung, and prostate cancer grading. Our study presents, discusses, and extracts the major trends from an exhaustive overview of various nuclei detection, segmentation, feature computation, and classification techniques used in histopathology imagery, specifically in hematoxylin-eosin and immunohistochemical staining protocols. This study also enables us to measure the challenges that remain, in order to reach robust analysis of whole slide images, essential high content imaging with diagnostic biomarkers and prognosis support in digital pathology.

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567 citations

Journal Article•DOI•

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

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Fuyong Xing¹, Lin Yang¹•Institutions (1)

University of Florida¹

06 Jan 2016-IEEE Reviews in Biomedical Engineering

TL;DR: A comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies is provided.

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Abstract: Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

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430 citations

Cites background from "Fast radial symmetry for detecting ..."

...[107] G. Loy and A. Zelinsky, “Fast radial symmetry for detecting points of interest,” IEEE Trans....
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...Fortunately, Loy and Zelinsky [107] have proposed a FRST to significantly decrease the time cost such that it is well suitable for real-time vision applications....
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...other in the clumps based on concave point detection and radialsymmetry-based voting [107]....
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References

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Open Access

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Journal Article•DOI•

Use of the Hough transformation to detect lines and curves in pictures

[...]

Richard O. Duda¹, Peter E. Hart¹•Institutions (1)

SRI International¹

01 Jan 1972-Communications of The ACM

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.

...read moreread less

Abstract: Hough has proposed an interesting and computationally efficient procedure for detecting lines in pictures. This paper points out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further. It also shows how the method can be used for more general curve fitting, and gives alternative interpretations that explain the source of its efficiency.

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6,693 citations

"Fast radial symmetry for detecting ..." refers background in this paper

...Kimme et al. [12] noted that on a circle boundary the edge orientation points toward oraway from thecenter of the circle, and used this to refine Duda and Hart’s technique and reduce the density of points mapped into the parameter space....
[...]
...Duda and Hart [8] showed how the Hough transform could be adapted to detect circles with an appropriate choice of parameter space....
[...]

Image Features From Phase Congruency

[...]

Peter Kovesi

01 Jan 1995

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.

...read moreread less

Abstract: Videre: Journal of Computer Vision Research (ISSN 1089-2788) is a quarterly journal published electronically on the Internet by The MIT Press, Cambridge, Massachusetts, 02142. Subscriptions and address changes should be addressed to MIT Press Journals, Five Cambridge Center, Cambridge, MA 02142; phone: (617) 253-2889; fax: (617) 577-1545; e-mail: journals-orders@mit.edu. Subscription rates are: Individuals $30.00, Institutions $125.00. Canadians add additional 7% GST. Prices subject to change without notice.

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1,186 citations

"Fast radial symmetry for detecting ..." refers background in this paper

...Each of the transforms was implemented in Matlab 5.3 (Kovesi’s symmetry from phase was implemented using Kovesi’s own Matlab code [15]) and the output computed....
[...]
...Comparing the results from this transform with those of Reisfeld’s generalized dark symmetry, we see that (as noted by Kovesi [13]) the latter is essentially a combined measure of the underlying symmetry and the contrast....
[...]
...Kovesi [13] presents a technique for determining local symmetry and asymmetry across an image from phase information....
[...]
...Kovesi’s symmetry from phase [13], ....
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...Minor and Skalansky’s implementation of the Circular Hough transform [19], Kovesi’s symmetry from phase was calculated for six filter orientations and four scales ranging from 2 to 24 pixels in diameter....
[...]

Journal Article•DOI•

Finding circles by an array of accumulators

[...]

Carolyn Kimme¹, Dana H. Ballard¹, Jack Sklansky¹•Institutions (1)

University of California, Irvine¹

01 Feb 1975-Communications of The ACM

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.

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Abstract: We describe an efficient procedure for detecting approximate circles and approximately circular arcs of varying gray levels in an edge-enhanced digitized picture. This procedure is an extension and improvement of the circle-finding concept sketched by Duda and Hart [2] as an extension of the Hough straight-line finder [6].

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624 citations

"Fast radial symmetry for detecting ..." refers methods in this paper

...[12] noted that on a circle boundary the edge orientation points toward oraway from thecenter of the circle, and used this to refine Duda and Hart’s technique and reduce the density of points mapped into the parameter space....
[...]
...The approach was inspired by the results of the generalized symmetry transform [24], [9], [25], although the final method bares more similarity to the work of Sela and Levine [28] and the circular Hough transform [12], [19]....
[...]
...Unlike previous techniques that have used this approach [12], [19], [28], it does not require the gradient to be quantized into angular bins, the contribution of every orientation is computed in a single pass over the image....
[...]

Journal Article•DOI•

Algorithms for defining visual regions-of-interest: comparison with eye fixations

[...]

C.M. Privitera¹, L.W. Stark¹•Institutions (1)

University of California, Berkeley¹

01 Sep 2000-IEEE Transactions on Pattern Analysis and Machine Intelligence

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.

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Abstract: Many machine vision applications, such as compression, pictorial database querying, and image understanding, often need to analyze in detail only a representative subset of the image, which may be arranged into sequences of loci called regions-of-interest (ROIs). We have investigated and developed a methodology that serves to automatically identify such a subset of aROIs (algorithmically detected ROIs) using different image processing algorithms (IPAs), and appropriate clustering procedures. In human perception, an internal representation directs top-down, context-dependent sequences of eye movements to fixate on similar sequences of hROIs (human identified ROIs). In the paper, we introduce our methodology and we compare aROIs with hROIs as a criterion for evaluating and selecting bottom-up, context-free algorithms. An application is finally discussed.

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585 citations

"Fast radial symmetry for detecting ..." refers background in this paper

...Stark and Pritevera [21], [22] compared the responses of a number of artificial region of interest detectors, including Reisfeld’s generalized symmetry transform [24], with regions of interest detected by human subjects....
[...]

Journal Article•DOI•

Context-free attentional operators: the generalized symmetry transform

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Daniel Reisfeld¹, Haim J. Wolfson¹, Yehezkel Yeshurun¹•Institutions (1)

Tel Aviv University¹

01 Mar 1995-International Journal of Computer Vision

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.

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Abstract: Active vision systems, and especially foveated vision systems, depend on efficient attentional mechanisms. We propose that machine visual attention should consist of both high-level, context-dependent components, and low-level, context free components. As a basis for the context-free component, we present an attention operator based on the intuitive notion of symmetry, which generalized many of the existing methods of detecting regions of interest. It is a low-level operator that can be applied successfully without a priori knowledge of the world. The resultingsymmetry edge map can be applied in various low, intermediate-and high- level tasks, such as extraction of interest points, grouping, and object recognition. In particular, we have implemented an algorithm that locates interest points in real time, and can be incorporated in active and purposive vision systems. The results agree with some psychophysical findings concerning symmetry as well as evidence concerning selection of fixation points. We demonstrate the performance of the transform on natural, cluttered images.

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434 citations

"Fast radial symmetry for detecting ..." refers background or methods in this paper

...This transform highlights regions of high contrast and local radial symmetry and has been applied to detecting facial features [24], [9], [25]....
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...The traditional approach to local symmetry detection [6], [24], [28] is to calculate the symmetry apparent in a local neighborhood about each point....
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...[24] or requiring multiple calculations for different gradient orientations, as do many other methods [6], [13], [19], [28]....
[...]
...Stark and Pritevera [21], [22] compared the responses of a number of artificial region of interest detectors, including Reisfeld’s generalized symmetry transform [24], with regions of interest detected by human subjects....
[...]
...[24], and the magnitude of the gradient is also taken into consideration....
[...]