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检索条件"任意字段=1st IEEE Workshop on Variational and Level Set Methods in Computer Vision"

共 33 条记录，以下是1-10 订阅

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RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples

RD-DPP: Rate-Distortion Theory Meets Determinantal Point Pro...

引用

ieee workshop on Applications of computer vision (WACV)

作者： Xiwen Chen Huayu Li Peijie Qiu Wenhui Zhu Rahul Amin Abolfazl Razi Clemson University University of Arizona Washington University in St. Louis Arizona State University MIT Lincoln Laboratory

ISBN: (数字)9798331510831

ISBN: (纸本)9798331510848

Selecting representative samples plays an indispensable role in many machine learning and computer vision applications under limited resources (e.g., limited communication bandwidth and computational power). Determinantal Point Process (DPP) is a widely used method for selecting the most diverse representative samples that can summarize a dataset. However, its adaptability to different tasks remains an open challenge, as it is challenging for DPP to perform task-specific tuning. In contrast, Rate-Distortion (RD) theory provides a way to measure task-specific diversity. However, optimizing RD for a data selection problem remains challenging because the quantity that needs to be optimized is the index set of the selected samples. To tackle these challenges, we first draw an inherent relationship between DPP and RD theory. Our theoretical derivation paves the way to take advantage of both RD and DPP for a task-specific data selection. To this end, we propose a novel method for task-specific data selection for multi-level classification tasks, named RD-DPP. Empirical studies on seven different datasets using five benchmark models demonstrate the effectiveness of the proposed RD-DPP method. Our method also outperforms recent strong competing methods, while exhibiting high generalizability to a variety of learning tasks. The source code is available on https://***/xiwencl/RD-DPP 1 .

关键词： Training computer vision Source coding Rate-distortion Data visualization Machine learning Bandwidth Benchmark testing Indexes Tuning

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Parsing R-CNN for Instance-level Human Analysis 32

Parsing R-CNN for Instance-Level Human Analysis

引用

32nd ieee/CVF Conference on computer vision and Pattern Recognition (CVPR)

作者： Yang, Lu Song, Qing Wang, Zhihui Jiang, Ming Beijing Univ Posts & Telecommun Beijing Peoples R China WiWide Inc Beijing Peoples R China

ISBN: (纸本)9781728132938

Instance-level human analysis is common in real-life scenarios and has multiple manifestations, such as human part segmentation, dense pose estimation, human-object interactions, etc. Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance. In this paper, we present an end-to-end pipeline for solving the instance-level human analysis, named Parsing R-CNN. It processes a set of human instances simultaneously through comprehensive considering the characteristics of region-based approach and the appearance of a human, thus allowing representing the details of instances. Parsing R-CNN is very flexible and efficient, which is applicable to many issues in human instance analysis. Our approach outperforms all state-of-the-art methods on CIHP (Crowd Instance-level Human Parsing), MHP v2.0 (Multi-Human Parsing) and DensePose-COCO datasets. Based on the proposed Parsing R-CNN, we reach the 1st place in the COCO 2018 Challenge DensePose Estimation task. Code and models are publicly available(1).

关键词： And Body Pose Categorization Deep Learning Face Gesture Grou Recognition: Detection Retrieval Segmentation

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Parsing R-CNN for Instance-level Human Analysis

Parsing R-CNN for Instance-Level Human Analysis

引用

ieee/CVF Conference on computer vision and Pattern Recognition

作者： Lu Yang Qing Song Zhihui Wang Ming Jiang Beijing University of Posts and Telecommunications WiWide Inc

ISBN: (纸本)9781728132945

关键词： Parsing Human

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Implementation of intelligent motor speed control using rotary encoder

Implementation of intelligent motor speed control using rota...

引用

1st International Conference on Robot, vision and Signal Processing, RVSP 2011

作者： Chao, Min Hsieh, Kunta Wang, Chin-Yu Chang, Hsinchiu Department of Civil Engineering and Engineering Informatics Cheng Shiu University Kaohsiung Taiwan Institute of Mechatronics Engineering Cheng Shiu University Kaohsiung Taiwan Graduate Institute of Mechatronics Engineering Cheng Shiu University Kaohsiung Taiwan Department of Computer Science and Information Engineering Cheng Shiu University Kaohsiung Taiwan

ISBN: (纸本)9780769545813

The project will try to implement the system with the NI Labview DAQ-6211 capture card to make intelligent motor speed control system, expect this architecture to learn new construction methods, and can develop new applications. Ideas in the hope of a simple feedback information, that is, to determine whether the current speed should be to accelerate or decelerate the motor commands. As the motor control system uses a PWM signal, so the time interval within the same time continuing the level of the signal width is different from the motor speed will result in different. We make a default speed under the control of motor speed in Labview to automatically achieve, so constantly adjust the speed target, the system will change the speed at any time, in order to achieve the set target speed. © 2011 ieee.

关键词： Speed

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A new method of dynamic texture segmentation based on optical flow and level set combination

A new method of dynamic texture segmentation based on optica...

引用

1st International Conference on Information Science and Engineering, ICISE2009

作者： Quan, Hongyan Institute of Software Engineering East China Normal University Shanghai China

ISBN: (纸本)9780769538877

Dynamic texture is a part of the natural scene. Dynamic texture segmentation issue is research hotspot in the field of computer vision and even robot research area. This paper presents a new dynamic texture recognition method based on level set strategy. The level set function evolutes to the boundary of objects according the optical flow feature of moving objects. Because we use the optical flow based terminal condition, the evolution can fast stop to the edge of dynamic texture object. The new method has the characteristic of fast and accuracy. It overcomes the shortcoming of reinitializing and slow evolution speed in the existing methods. The experimental results show that the method can effectively achieve the dynamic texture segmentation of moving objects and it is a very useful method. ©2009 ieee.

关键词： Optical flows

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Otolith image analysis by computer vision

Otolith image analysis by computer vision

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1st International Conference on Bio-Inspired Systems and Signal Processing

作者： Chessel, Anatole Fablet, Ronan Kervrann, Charles Cao, Frederic IFREMER/LASAA France IRISA/VISTA France

ISBN: (纸本)9789898111180

Otoliths are small stone located in fish inner ears and characterised by an accretionnary growth. They act as a biological archive and are of much use in marine biology and ecology. In this article a computer vision framework is presented which recover the successive shapes of the otolith and the significant ridges and valleys from a 2D grayscale image. Seeing vision processes as complex systems, an iterated process is presented using two perceptual information, contrast and good continuity. The successive concentric shapes of the otoliths are recovered as the level-sets of a dome shaped potential function, computed in a variational framework. Potential applications includes in particular fish age estimation, otoliths morphogenesis modelling, otolith proxy fusion.

关键词： computer vision otolith fish biology and ecology biological image analysis detection a contrario variational methods

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Piecewise constant level set method for 3D image segmentation

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Losnegard, Are Christiansen, Oddvar Tai, Xue-Cheng Univ Bergen Dept Math Johannes Brunsgate 12 N-5007 Bergen Norway

ISBN: (纸本)9783540728221

level set methods have been proven to be efficient tools for tracing interface problems. Recently;some variants of the Osher- sethian level set methods, which are called the Piecewise Constant level set methods (PCLSM), have been proposed for some interface problems. The methods need to minimize a smooth cost functional under some special constraints. In this paper a PCLSM for 3D image segmentation is tested. The algorithm uses the gradient descent method combined with a Quasi-Newton method to minimize an augmented Lagrangian functional. Experiments for medical image segmentation are shown on synthetic three dimensional MR brain images. The efficiency of the algorithm and the quality of the obtained images are demonstrated.

关键词： Image segmentation

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Solving the Chan-Vese model by a multiphase level set algorithm based on the topological derivative

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： He, Lin Osher, stanley Johann Radon Inst Computat & Appl Math A-4040 Linz Austria Univ Calif Los Angeles Dept Mat Los Angeles CA 90095 USA

ISBN: (纸本)9783540728221

In this work, we specifically solve the Chan-Vese active contour model by multiphase level set methods. We first develop a fast algorithm based on calculating the variational energy of the Chan-Vese model without the length term. We check whether the energy decreases or not when we move a point to another segmented region. Then we draw a connection between this algorithm and the topological derivative, a concept emerged from the shape optimization field. Furthermore, to include the length terra of the Chan-Vese model;we apply a preprocessing step on the image by using nonlinear diffusion. We show numerical experiments to demonstrate the efficiency and the robustness of our algorithm.

关键词： image segmentation level set methods Chan-Vese model topological derivative

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level set methods for watershed image segmentation

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Tai, Xue-Cheng Hodneland, Erlend Weickert, Joachim Bukoreshtliev, Nickolay V. Lundervold, Arvid Gerdes, Hans-Hermann Univ Bergen Dept Math Johannes Brusgate 12 Bergen Norway Univ Bergen Dept Biomed N-5009 Bergen Norway Univ Saarland Fac Math & Comp Sci D-66041 Saarbrucken Germany

ISBN: (纸本)9783540728221

In this work a marker-controlled and regularized watershed segmentation is proposed. Only a few previous studies address the task of regularizing the obtained watershed lines from the traditional marker-controlled watershed segmentation. In the present formulation, the topographical distance function is applied in a level set formulation to perform the segmentation, and the regularization is easily accomplished by regularizing the level set functions. Based on the well-known Four-Color theorem, a mathematical model is developed for the proposed ideas. With this model, it is possible to segment any 2D image with arbitrary number of phases with as few as one or two level set functions. The algorithm has been tested on real 2D fluorescence microscopy images displaying rat cancer cells, and the algorithm has also been compared to a standard watershed segmentation as it is implemented in MATLAB. For a fixed set of markers and a fixed set of challenging images, the comparison of these two methods shows that the present level set formulation performs better than a standard watershed segmentation.

关键词： Watersheds

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Detecting regions of dynamic texture

引用

1st International Conference on Scale Space and variational methods in computer vision

作者： Amiaz, Tomer Fazekas, Sandor Chetverikov, Dmitry Kiryati, Nahum Tel Aviv Univ Sch Elect Engn IL-69978 Tel Aviv Israel Comp & Automat Res Inst Budapest Hungary

ISBN: (纸本)9783540728221

Motion estimation is usually based on the brightness constancy assumption. This assumption holds well for rigid objects with a Lambertian surface, but it is less appropriate for fluid and gaseous materials. For these materials a variant of this assumption, which we call the brightness conservation assumption should be employed. Under this assumption an object's brightness can diffuse to its neighborhood. We propose a method for detecting regions of dynamic texture in image sequences. Segmentation into regions of static and dynamic texture is achieved by using a level set scheme. The level set function separates the images into areas obeying brightness constancy and those which obey brightness conservation. Experimental results on challenging image sequences demonstrate the success of the segmentation scheme and validate the model.

关键词： dynamic texture level set optical flow

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