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检索条件"任意字段=2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006"

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WiCV 2018: The Fourth Women In computer vision Workshop 31

WiCV 2018: The Fourth Women In Computer Vision Workshop

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Demir, Ilke Bazazian, Dena Romero, Adriana Sharmanska, Viktoriia Tchapmi, Lyne P. Facebook Menlo Pk CA 94025 USA Comp Vis Ctr Barcelona Spain Facebook AI Res Montreal PQ Canada Imperial Coll London London England Stanford Univ Stanford CA 94305 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

We present WiCV 2018 - Women in computer vision Workshop to increase the visibility and inclusion of women researchers in computer vision field, organized in conjunction with cvpr 2018. computer vision and machine learning have made incredible progress over the past years, yet the number of female researchers is still low both in academia and industry. WiCV is organized to raise visibility of female researchers, to increase the collaboration, and to provide mentorship and give opportunities to female-identifying junior researchers in the field. In its fourth year, we are proud to present the changes and improvements over the past years, summary of statistics for presenters and attendees, followed by expectations from future generations.

关键词： conferences computer vision Industries Object recognition Engineering profession Collaboration Machine learning

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Graph Laplacian kernels for object classification from a single example

Graph Laplacian kernels for object classification from a sin...

引用

2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Chang, Hong Yeung, Dit-Yan Department of Computer Science Hong Kong University of Science and Technology

ISBN: (纸本)0769525970

Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this problem in the context of specific applications, very little work has been done so far on the problem under more general object classification settings. In this paper, we propose a graph-based approach to the problem. Based on a robust path-based similarity measure proposed recently, we construct a weighted graph using the robust path-based similarities as edge weights. A kernel matrix, called graph Laplacian kernel, is then defined based on the graph Laplacian. With the kernel matrix, in principle any kernel-based classifier can be used for classification. In particular, we demonstrate the use of a kernel nearest neighbor classifier on some synthetic data and real-world image sets, showing that our method can successfully solve some difficult classification tasks with only very few labeled examples. © 2006 ieee.

关键词： Graph theory

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What is the set of images of an object under all possible lighting conditions?

What is the set of images of an object under all possible li...

引用

1966 ieee computer society conference on computer vision and pattern recognition

作者： Belhumeur, PN Kriegman, DJ YALE UNIV DEPT ELECT ENGNNEW HAVENCT 06520

ISBN: (纸本)0818672587

The appearance of a particular object depends on both the viewpoint from which it is observed and the light sources by which it is illuminated. If the appearance of two objects is never identical for any pose or lighting conditions, then - in theory - the objects can always be distinguished or recognized. The question arises: What is the set of images of an object under all lighting conditions and pose? In this paper, we consider only the set of images of an object under variable illumination (including multiple, extended light sources and attached shadows). We prove that the set of n-pixel images of a convex object with a Lambertian reflectance function, illuminated by an arbitrary number of point light sources at infinity, forms a convex polyhedral cone in Rⁿ and that the dimension of this illumination cone equals the number of distinct surface normals. Furthermore, we show that the cone for a particular object can be constructed from three properly chosen images. Finally, we prove that the set of n-pixel images of an object of any shape and with an arbitrary reflectance function, seen under all possible illumination conditions, still forms a convex cone in Rⁿ. These results immediately suggest certain approaches to object recognition. Throughout this paper, we offer results demonstrating the empirical validity of the illumination cone representation.

关键词： Object recognition

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Learning object shape: From drawings to images

Learning object shape: From drawings to images

引用

2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Elidan, Gal Heitz, Geremy Koller, Daphne Dept. of Computer Science Stanford University Dept. of Electrical Engineering Stanford University

ISBN: (纸本)0769525970

We consider the important challenge of recognizing a variety of deformable object classes in images. Of fundamental importance and particular difficulty in this setting is the problem of "outlining" an object, rather than simply deciding on its presence or absence. A major obstacle in learning a model that will allow us to address this task is the need for hand-segmented training images. In this paper we present a novel landmark-based, piecewise-linear model of the shape of an object class. We then formulate a learning approach that allows us to learn this model with minimal user supervision. We circumvent the need for hand-segmentation by transferring the shape "essence" of an object from drawings to complex images. We show that our method is able to automatically and effectively learn and localize a variety of object classes. © 2006 ieee.

关键词： Learning systems

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Image velocity estimation from trajectory surface in spatiotemporal space

Image velocity estimation from trajectory surface in spatiot...

引用

1997 ieee computer society conference on computer vision and pattern recognition (cvpr 97)

作者： Otsuka, K Horikoshi, T Suzuki, S NTT Human Interface Lab Yokosuka Japan

ISBN: (纸本)0818678224;0780342364

A new framework and method, based on image motion trajectories in spatiotemporal space(x-y-t space), are proposed to estimate image velocity from an image sequence. We focus on the surfaces of the trajectories in the x-y-t space formed by the edges and contours of moving objects and obtain image velocity from the orientation of the intersection line formed by tangent planes on the trajectories. The proposed method includes two Hough transforms to detect the most dominant orientation in all possible intersection lilies and reliably produces the dominant translational image velocity semi-locally. Also, the confidence measure of estimates is defined to decide the optimal size of patch that suppresses the aperture problem. Experimental results from several synthetic and real image sequences are presented to verify the effectiveness of the method and to confirm its robustness against noise and occlusion.

关键词： Object recognition

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Robust recognition of scaled eigenimages through a hierarchical approach

Robust recognition of scaled eigenimages through a hierarchi...

引用

1998 ieee computer-society conference on computer vision and pattern recognition

作者： Bischof, H Leonardis, A Vienna Tech Univ Pattern Recog & Image Proc Grp A-1040 Vienna Austria

ISBN: (纸本)0818684976

Recently, rue have proposed a new approach to estimation of the coefficients of eigenimages, which is robust against occlusion, varying background: and other types of non-Gaussian noise [4, 5]. In this paper we show that our method for estimating the coefficients can be applied to convolved and subsampled images yielding the same value of the coefficients. This enables an efficient multiresolution approach, where the values of the coefficients can directly be propagated through the scales. This property is used to extend oar robust method to the problem of scaled images. We performed extensive experimental evaluations to confirm, our theoretical results.

关键词： Object recognition

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Using stationary-dynamic camera assemblies for wide-area video surveillance and selective attention

Using stationary-dynamic camera assemblies for wide-area vid...

引用

2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Jain, Ankur Kopell, Dan Kakligian, Kyle Wang, Yuan-Fang Department of Computer Science University of California Santa Barbara CA 93106

ISBN: (纸本)0769525970

In this paper, we present a prototype video surveillance system that uses stationary-dynamic (or master-slave) camera assemblies to achieve wide-area surveillance and selective focus-of-attention. We address two critical issues in deploying such camera assemblies in real-world applications: off-line camera calibration and on-line selective focus-of-attention. Our contributions over existing techniques are twofold: (1) in terms of camera calibration, our technique calibrates all degrees-of-freedom (DOFs) of both stationary and dynamic cameras, using a closed-form solution that is both efficient and accurate, and (2) in terms of selective focus-of-attention, our technique correctly handles dynamic changes in the scene and varying object depths. This is a significant improvement over existing techniques that use an expensive and non-adaptable table-look-up process. © 2006 ieee.

关键词： Video cameras

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Symmetry Detection from Real World Images Competition 2013: Summary and Results

Symmetry Detection from Real World Images Competition 2013: ...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Liu, Jingchen Slota, George Zheng, Gang Wu, Zhaohui Park, Minwoo Lee, Seungkyu Rauschert, Ingmar Liu, Yanxi Penn State Univ University Pk PA 16802 USA Object Video San Antonio TX USA Samsung Res Seoul South Korea

ISBN: (纸本)9780769549903

Symmetry is a pervasive phenomenon presenting itself in all forms and scales in natural and manmade environments. Its detection plays an essential role at all levels of human as well as machine perception. The recent resurging interest in computational symmetry for computer vision and computer graphics applications has motivated us to conduct a US NSF funded symmetry detection algorithm competition as a workshop affiliated with the computer vision and pattern recognition (cvpr) conference, 2013. This competition sets a more complete benchmark for computer vision symmetry detection algorithms. In this report we explain the evaluation metric and the automatic execution of the evaluation workflow. We also present and analyze the algorithms submitted, and show their results on three test sets of real world images depicting reflection, rotation and translation symmetries respectively. This competition establishes a performance baseline for future work on symmetry detection.

关键词： computer graphics computer vision

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A refractive camera for acquiring stereo and super-resolution images

A refractive camera for acquiring stereo and super-resolutio...

引用

2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Chunyu, Gao Ahuja, Narendra Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign

ISBN: (纸本)0769525970

We propose a novel depth sensing system composed of a single camera, and a transparent plate which is placed in front of the camera and rotates about the optical axis of the camera. The camera takes a sequence of images as the plate rotates, which provide the equivalent of a large number of stereo pairs. Compared with conventional multi-camera stereo systems, the use of a single camera for capturing stereo pairs helps improve the accuracy of detecting correspondences. The availability of the large number of stereo pairs also reduces matching ambiguities, even for objects with low texture. By using both the images and the estimated depth map, we show that the proposed system is also capable of generating super-resolution images. Experimental results on reconstructing 3D structures and recovering high-resolution images are presented. © 2006 ieee.

关键词： Cameras

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Seamless image stitching of scenes with large motions and exposure differences

Seamless image stitching of scenes with large motions and ex...

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2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Eden, Ashley Uyttendaele, Matthew Szeliski, Richard Computer Science Division U.C. Berkeley Interactive Visual Media Group Microsoft Research

ISBN: (纸本)0769525970

This paper presents a technique to automatically stitch multiple images at varying orientations and exposures to create a composite panorama that preserves the angular extent and dynamic range of the inputs. The main contribution of our method is that it allows for large exposure differences, large scene motion or other misregistrations between frames and requires no extra camera hardware. To do this, we introduce a two-step graph cut approach. The purpose of the first step is to fix the positions of moving objects in the scene. In the second step, we fill in the entire available dynamic range. We introduce data costs that encourage consistency and higher signal-to-noise ratios, and seam costs that encourage smooth transitions. Our method is simple to implement and effective. We demonstrate the effectiveness of our approach on several input sets with varying exposures and camera orientations. © 2006 ieee.

关键词： Image analysis

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