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Fast radial symmetry for detecting points of interest

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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.

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Citations
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Grape detection, segmentation, and tracking using deep neural networks and three-dimensional association

TL;DR: It is shown that for grape wines, a crop presenting large variability in shape, color, size and compactness, grape clusters can be successfully detected, segmented and tracked using state-of-the-art CNNs.
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Kinetics of dCas9 target search in Escherichia coli

TL;DR: The search mechanisms of the catalytically inactive Cas9 (dCas9) in living Escherichia coli are studied by combining single-molecule fluorescence microscopy and bulk restriction-protection assays to show that it takes 6 hours to find its target sequence, with each potential target bound for less than 30 ms.
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Research Advances and Challenges of Autonomous and Connected Ground Vehicles

TL;DR: A representative architecture of CAVs is introduced and the latest research advances, methods, and algorithms for sensing, perception, planning, and control of CAV are surveyed and their significant research issues enumerated.
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Driver Inattention Detection based on Eye Gaze-Road Event Correlation

TL;DR: It is shown that it is possible to detect missed road events and warn the driver appropriately, and a prototype system capable of estimating the driver's observations and detecting driver inattentiveness is presented.
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Precedence of the eye region in neural processing of faces

TL;DR: Bottom-up face processing is relatively local and linearly integrates features—consistent with parts-based models—grounding investigation of how the presence of a face is first inferred in the IT face processing hierarchy.
References
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Journal ArticleDOI

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

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

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

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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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.