The Experts below are selected from a list of 17217 Experts worldwide ranked by ideXlab platform
Alexander Zelinsky - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Speed Sign Detection Using the Radial Symmetry Detector
IEEE Transactions on Intelligent Transportation Systems, 2008Co-Authors: Nick Barnes, Alexander Zelinsky, Luke S. FletcherAbstract:Algorithms for classifying road signs have a high computational cost per pixel processed. A detection stage that has a lower computational cost can facilitate real-time processing. Various authors have used shape and color-based detectors. Shape-based detectors have an advantage under variable lighting conditions and sign deterioration that, although the apparent color may change, the shape is preserved. In this paper, we present the Radial Symmetry detector for detecting speed signs. We evaluate the detector itself in a system that is mounted within a road vehicle. We also evaluate its performance that is integrated with classification over a series of sequences from roads around Canberra and demonstrate it while running online in our road vehicle. We show that it can detect signs with high reliability in real time. We examine the internal parameters of the algorithm to adapt it to road sign detection. We demonstrate the stability of the system under the variation of these parameters and show computational speed gains through their tuning. The detector is demonstrated to work under a wide variety of visual conditions.
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real time Radial Symmetry for speed sign detection
IEEE Intelligent Vehicles Symposium, 2004Co-Authors: Nick Barnes, Alexander ZelinskyAbstract:Algorithms for classifying road signs have a high computational cost per pixel processed. A promising approach to real-time sign detection is to reduce the number of pixels to be classified as being a particular sign to a minimum by some form of sign detection on the image using less time expensive algorithms. In this paper, we adapt the fast Radial Symmetry detector to the image stream from a camera mounted in a car eliminate almost all non-sign pixels from the image stream. We then are able to apply normalised cross-correlation to classify the signs. This method is suitable for circular signs only; we apply it to Australian speed signs in this paper. Our results show that it is robust to a broad range of lighting conditions. Also, as the method is fast, there is no need to make unrealistic-ally strict assumptions about image structure.
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fast Radial Symmetry for detecting points of interest
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003Co-Authors: Alexander ZelinskyAbstract: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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a fast Radial Symmetry transform for detecting points of interest
European Conference on Computer Vision, 2002Co-Authors: Alexander ZelinskyAbstract:A new feature detection technique is presented that utilises local Radial Symmetry to identify regions of interest within a scene. This transform is significantly faster than existing techniques using Radial Symmetry and offers the possibility of real-time implementation on a standard processor. The new transformis shown to perform well on a wide variety of images and its performance is tested against leading techniques from the literature. Both as a facial feature detector and as a generic region of interest detector the new transformis seen to offer equal or superior performance to contemporary techniques whilst requiring drastically less computational effort.
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ECCV (1) - A Fast Radial Symmetry Transform for Detecting Points of Interest
Computer Vision — ECCV 2002, 2002Co-Authors: Alexander ZelinskyAbstract:A new feature detection technique is presented that utilises local Radial Symmetry to identify regions of interest within a scene. This transform is significantly faster than existing techniques using Radial Symmetry and offers the possibility of real-time implementation on a standard processor. The new transformis shown to perform well on a wide variety of images and its performance is tested against leading techniques from the literature. Both as a facial feature detector and as a generic region of interest detector the new transformis seen to offer equal or superior performance to contemporary techniques whilst requiring drastically less computational effort.
Nick Barnes - One of the best experts on this subject based on the ideXlab platform.
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Real-Time Speed Sign Detection Using the Radial Symmetry Detector
IEEE Transactions on Intelligent Transportation Systems, 2008Co-Authors: Nick Barnes, Alexander Zelinsky, Luke S. FletcherAbstract:Algorithms for classifying road signs have a high computational cost per pixel processed. A detection stage that has a lower computational cost can facilitate real-time processing. Various authors have used shape and color-based detectors. Shape-based detectors have an advantage under variable lighting conditions and sign deterioration that, although the apparent color may change, the shape is preserved. In this paper, we present the Radial Symmetry detector for detecting speed signs. We evaluate the detector itself in a system that is mounted within a road vehicle. We also evaluate its performance that is integrated with classification over a series of sequences from roads around Canberra and demonstrate it while running online in our road vehicle. We show that it can detect signs with high reliability in real time. We examine the internal parameters of the algorithm to adapt it to road sign detection. We demonstrate the stability of the system under the variation of these parameters and show computational speed gains through their tuning. The detector is demonstrated to work under a wide variety of visual conditions.
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real time Radial Symmetry for speed sign detection
IEEE Intelligent Vehicles Symposium, 2004Co-Authors: Nick Barnes, Alexander ZelinskyAbstract:Algorithms for classifying road signs have a high computational cost per pixel processed. A promising approach to real-time sign detection is to reduce the number of pixels to be classified as being a particular sign to a minimum by some form of sign detection on the image using less time expensive algorithms. In this paper, we adapt the fast Radial Symmetry detector to the image stream from a camera mounted in a car eliminate almost all non-sign pixels from the image stream. We then are able to apply normalised cross-correlation to classify the signs. This method is suitable for circular signs only; we apply it to Australian speed signs in this paper. Our results show that it is robust to a broad range of lighting conditions. Also, as the method is fast, there is no need to make unrealistic-ally strict assumptions about image structure.
Zhenli Huang - One of the best experts on this subject based on the ideXlab platform.
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fast and precise algorithm based on maximum Radial Symmetry for single molecule localization
Optics Letters, 2012Co-Authors: Fan Long, Shaoqun Zeng, Zhenli HuangAbstract:We present an algorithm to estimate the location of single fluorescent molecule with both high speed and high precision. This algorithm is based on finding the subpixel position with maximum Radial Symmetry in a pixelated single molecule fluorescence image. Compared with conventional algorithms, this algorithm does not rely on point-spread-function or noise model. Through numerical simulation and experimental analysis, we found that this algorithm exhibits localization precision very close to the maximum likelihood estimator (MLE), while executes ∼1000 times faster than the MLE and ∼6 times faster than the fluoroBancroft algorithm.
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fast and precise algorithm based on maximum Radial Symmetry for single molecule localization
Optics Letters, 2012Co-Authors: Fan Long, Shaoqun Zeng, Zhenli HuangAbstract:We present an algorithm to estimate the location of single fluorescent molecule with both high speed and high precision. This algorithm is based on finding the subpixel position with maximum Radial Symmetry in a pixelated single molecule fluorescence image. Compared with conventional algorithms, this algorithm does not rely on point-spread-function or noise model. Through numerical simulation and experimental analysis, we found that this algorithm exhibits localization precision very close to the maximum likelihood estimator (MLE), while executes ∼1000 times faster than the MLE and ∼6 times faster than the fluoroBancroft algorithm.
Fan Long - One of the best experts on this subject based on the ideXlab platform.
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fast and precise algorithm based on maximum Radial Symmetry for single molecule localization
Optics Letters, 2012Co-Authors: Fan Long, Shaoqun Zeng, Zhenli HuangAbstract:We present an algorithm to estimate the location of single fluorescent molecule with both high speed and high precision. This algorithm is based on finding the subpixel position with maximum Radial Symmetry in a pixelated single molecule fluorescence image. Compared with conventional algorithms, this algorithm does not rely on point-spread-function or noise model. Through numerical simulation and experimental analysis, we found that this algorithm exhibits localization precision very close to the maximum likelihood estimator (MLE), while executes ∼1000 times faster than the MLE and ∼6 times faster than the fluoroBancroft algorithm.
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fast and precise algorithm based on maximum Radial Symmetry for single molecule localization
Optics Letters, 2012Co-Authors: Fan Long, Shaoqun Zeng, Zhenli HuangAbstract:We present an algorithm to estimate the location of single fluorescent molecule with both high speed and high precision. This algorithm is based on finding the subpixel position with maximum Radial Symmetry in a pixelated single molecule fluorescence image. Compared with conventional algorithms, this algorithm does not rely on point-spread-function or noise model. Through numerical simulation and experimental analysis, we found that this algorithm exhibits localization precision very close to the maximum likelihood estimator (MLE), while executes ∼1000 times faster than the MLE and ∼6 times faster than the fluoroBancroft algorithm.
Guotao Wang - One of the best experts on this subject based on the ideXlab platform.
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Radial Symmetry for a generalized nonlinear fractional p-Laplacian problem
Nonlinear Analysis: Modelling and Control, 2021Co-Authors: Wenwen Hou, Lihong Zhang, Ravi P. Agarwal, Guotao WangAbstract:This paper first introduces a generalized fractional p-Laplacian operator (–Δ)sF;p. By using the direct method of moving planes, with the help of two lemmas, namely decay at infinity and narrow region principle involving the generalized fractional p-Laplacian, we study the monotonicity and Radial Symmetry of positive solutions of a generalized fractional p-Laplacian equation with negative power. In addition, a similar conclusion is also given for a generalized Hénon-type nonlinear fractional p-Laplacian equation.
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Radial Symmetry of standing waves for nonlinear fractional laplacian hardy schrodinger systems
Applied Mathematics Letters, 2020Co-Authors: Guotao Wang, Xueyan RenAbstract:Abstract In this paper, by applying the direct method of moving planes, the authors study the Radial Symmetry of standing waves for nonlinear fractional Laplacian Schrodinger systems with Hardy potential. Firstly, under the condition of infinite decay, the Radial Symmetry of the solution is established. Secondly, under the condition of no decay, the Radial Symmetry and non-existence of solution are established by the Kelvin transform.
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Radial Symmetry of solution for fractional p laplacian system
Nonlinear Analysis-theory Methods & Applications, 2020Co-Authors: Lihong Zhang, Guotao Wang, Bashir AhmadAbstract:Abstract In this paper, we investigate the method of moving planes for fractional p -Laplacian system. We firstly discuss the key ingredients for the method of moving planes such as maximum principle for anti-symmetric functions, decay at infinity and boundary estimate. Then we apply the method of moving planes to establish the Radial Symmetry and the monotonicity of the positive solutions for fractional p − Laplacian system in a unit ball or in the whole space.
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Radial Symmetry of standing waves for nonlinear fractional Laplacian Hardy–Schrödinger systems
Applied Mathematics Letters, 2020Co-Authors: Guotao Wang, Xueyan RenAbstract:Abstract In this paper, by applying the direct method of moving planes, the authors study the Radial Symmetry of standing waves for nonlinear fractional Laplacian Schrodinger systems with Hardy potential. Firstly, under the condition of infinite decay, the Radial Symmetry of the solution is established. Secondly, under the condition of no decay, the Radial Symmetry and non-existence of solution are established by the Kelvin transform.
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Radial Symmetry of solution for fractional p−Laplacian system
Nonlinear Analysis, 2020Co-Authors: Lihong Zhang, Guotao Wang, Bashir Ahmad, Xueyan RenAbstract:Abstract In this paper, we investigate the method of moving planes for fractional p -Laplacian system. We firstly discuss the key ingredients for the method of moving planes such as maximum principle for anti-symmetric functions, decay at infinity and boundary estimate. Then we apply the method of moving planes to establish the Radial Symmetry and the monotonicity of the positive solutions for fractional p − Laplacian system in a unit ball or in the whole space.