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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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Expanding Disparity Range in an FPGA Stereo System While Keeping Resource Utilization Low

Expanding Disparity Range in an FPGA Stereo System While Kee...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： D.K. Masrani W.J. MacLean Department of Electrical and Computer Engineering University of Toronto Toronto ONT Canada

Field Programmable Gate Array devices (FPGAs) are attractive for implementing computer vision algorithms due to the fact that they allow the designer to exploit the parallel nature of many vision algorithms, thus offering substantial speed improvements over fixed hardware/software systems. One major drawback, however, is that adding resources to reconfigurable devices is not as simple as adding memory or upgrading a hard disk. This becomes a problem when adapting a system to deal with larger image sizes or, in the case of stereo disparity estimation, larger disparity ranges (parameter ranges in general). This paper describes preliminary work on a design to expand the disparity range and input image size of an existing FPGA-based stereo system [8] while not significantly expanding resource requirements. Simulations on synthetic and real images are given, as well as a description of the proposed architecture changes in porting the system to a newer FPGA architecture.

关键词： Field programmable gate arrays Resource management Stereo vision Hardware computer vision Application software Software algorithms computer architecture Logic devices Circuits

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Visibility constrained surface evolution

Visibility constrained surface evolution

引用

conference on computer vision and pattern recognition (cvpr)

作者： J.E. Solem F. Kahl A. Heyden Applied Mathematics Group School of Technology and Society Malmö University Sweden Department of Computer Science & Engineering University of California La Jolla CA USA

The problem of feature-based surface reconstruction is considered in this paper. Our main contribution is the ability to handle visibility constraints, obtained from the projections of points, curves and silhouettes, in the surface fitting process. While traditional methods often ignore such information, we show that visibility constraints not only give better initial surface estimates and faster convergence, but also provide an important cue for determining surface topology. The problem is cast as a variational problem with constraints within the level set framework. It is shown how to evolve the surface without violating the visibility constraints using methods from variational calculus. Applications of the theory are detailed for a number of important cases of geometric primitives: points, curves and visual hulls. Several experiments on real image sequences are given to demonstrate the performance of the approach.

关键词： Surface fitting Surface reconstruction Layout Level set Image reconstruction Topology Cameras Clouds Mathematics computer science

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Multi-view stereo via volumetric graph-cuts

Multi-view stereo via volumetric graph-cuts

引用

conference on computer vision and pattern recognition (cvpr)

作者： G. Vogiatzis P.H.S. Torr R. Cipolla Department of Engineering University of Cambridge Cambridge UK Department of Computing Oxford Brookes University Wheatley Oxfordshire UK

This paper presents a novel formulation for the multi-view scene reconstruction problem. While this formulation benefits from a volumetric scene representation, it is amenable to a computationally tractable global optimisation using Graph-cuts. The algorithm proposed uses the visual hull of the scene to infer occlusions and as a constraint on the topology of the scene. A photo consistency-based surface cost functional is defined and discretised with a weighted graph. The optimal surface under this discretised functional is obtained as the minimum cut solution of the weighted graph. Our method provides a viewpoint independent surface regularisation, approximate handling of occlusions and a tractable optimisation scheme. Promising experimental results on real scenes as well as a quantitative evaluation on a synthetic scene are presented.

关键词： Layout Surface reconstruction Image reconstruction Topology Geometry Pixel Stereo vision Cost function Optimization methods computer vision

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Identifying semantically equivalent object fragments

Identifying semantically equivalent object fragments

引用

conference on computer vision and pattern recognition (cvpr)

作者： B. Epshtein S. Ullman Weizmann Institute of Science Rehovot Israel

We describe a novel technique for identifying semantically equivalent parts in images belonging to the same object class, (e.g. eyes, license plates, aircraft wings etc.). The visual appearance of such object parts can differ substantially, and therefore, traditional image similarity-based methods are inappropriate for this task. The technique we propose is based on the use of common context. We first retrieve context fragments, which consistently appear together with a given input fragment in a stable geometric relation. We then use the context fragments in new images to infer the most likely position of equivalent parts. Given a set of image examples of objects in a class, the method can automatically learn the part structure of the domain - identify the main parts, and how their appearance changes across objects in the class. Two applications of the proposed algorithm are shown: the detection and identification of object parts and object recognition.

关键词： Object recognition Object detection Licenses Face detection Nose Speech recognition computer science Mathematics Eyes Aircraft

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Fusion-Based Background-Subtraction using Contour Saliency

Fusion-Based Background-Subtraction using Contour Saliency

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： J.W. Davis V. Sharma Department of Computer Science and Engineering Ohio State Uinversity Columbus OH USA

We present a new contour-based background-subtraction technique using thermal and visible imagery for persistent object detection in urban settings. Statistical backgroundsubtraction in the thermal domain is used to identify the initial regions-of-interest. Color and intensity information are used within these areas to obtain the corresponding regionsof- interest in the visible domain. Within each region, input and background gradient information are combined to form a Contour Saliency Map. The binary contour fragments, obtained from corresponding Contour Saliency Maps, are then combined. An A path-constrained search along watershed boundaries is used to complete and close any broken contour segments. Lastly, the contour image is flood- filled to produce silhouettes. Results of our approach are presented and compared against manually segmented data.

关键词： Object detection Cameras Layout Thermal sensors Image segmentation Lighting Temperature sensors computer vision computer science Thermal engineering

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Restoration and recognition in a loop

Restoration and recognition in a loop

引用

conference on computer vision and pattern recognition (cvpr)

作者： M.D. Gupta S. Rajaram N. Petrovic T.S. Huang Beckman Institute University of Illinois Urbana-Champaign IL USA Siemens Corporate Research Inc. Princeton NJ USA

In this paper we present a novel learning based method for restoring and recognizing images of digits that have been blurred using an unknown kernel. The novelty of our work is an iterative loop that alternates between recognition and restoration stages. In the restoration stage we model the image as an undirected graphical model over the image patches with the compatibility functions represented as non-parametric kernel densities. Compatibility functions are initially learned using uniform random samples from the training data. We solve the inference problem by an extended version of the non-parametric belief propagation algorithm in which we introduce the notion of partial messages. We close the loop by using the confidence scores of the recognition to non-uniformly sample from the training set in order to retrain the compatibility functions. We show experimental results on synthetic and license plate images.

关键词： Image restoration Image resolution Learning systems Kernel Wiener filter Machine learning Image recognition Licenses computer vision Bayesian methods

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Radiometric Compensation in a Projector-Camera System Based Properties of Human vision System

Radiometric Compensation in a Projector-Camera System Based ...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Dong Wang I. Sato T. Okabe Y. Sato Institute of Industrial Science University of Tokyo Tokyo Japan

We introduce a novel technique for performing radiometric compensation for a projector-camera system that projects images onto a textured planar surface, which is designed to minimize perceptual artifacts visible to observers according to a model of the human vision system. A projector-camera system has previously been proposed for projecting images onto an arbitrary surface using radiometric compensation, however the dynamic range of a projector is physically limited there are some textures that cannot be compensated correctly. Also, human eyes are sensitive to artifacts introduced in this way. Our technique is designed to provide compensated images with perceptually less noticeable artifacts while preserving enough brightness and contrast in the output. We develop an optimization framework based on a perceptually-based physical error metric to minimize perceptible artifacts in the final compensated images by compressing the contrast of the input images.

关键词： Radiometry Humans Machine vision Dynamic range Brightness Displays Surface texture Image coding Eyes Photometry

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DISTATIS: The Analysis of Multiple Distance Matrices

DISTATIS: The Analysis of Multiple Distance Matrices

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： H. Abdi A.J. O'Toole D. Valentin B. Edelman University of Texas Dallas Richardson TX USA Université de Bourgogne France University of Texas Dallas USA

In this paper we present a generalization of classical multidimensional scaling called DISTATIS which is a new method that can be used to compare algorithms when their outputs consist of distance matrices computed on the same set of objects. The method first evaluates the similarity between algorithms using a coefficient called the RV coefficient. From this analysis, a compromise matrix is computed which represents the best aggregate of the original matrices. In order to evaluate the differences between algorithms, the original distance matrices are then projected onto the compromise. We illustrate this method with a "toy example" in which four different "algorithms" (two computer programs and two sets of human observers) evaluate the similarity among faces.

关键词： Multidimensional systems Face recognition Aggregates Humans Object recognition Performance evaluation Testing Cognition Neuroscience Time measurement

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Learning discriminant features for multi-view face and eye detection

Learning discriminant features for multi-view face and eye d...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Peng Wang Qiang Ji Department of Electrical Computer and System Engineering Rensselaer Polytechnic Institute Troy NY USA

In current face detection, mostly often used features are selected from a large set (e.g. Haar wavelets). Generally Haar wavelets only represent the local geometric feature. When applying those features to profile faces and eyes with irregular geometric patterns, the classifier accuracy is low in the later training stages, only near 50%. In this paper, instead of brute-force searching the large feature set, we propose to statistically learn the discriminant features for object detection. Besides applying Fisher discriminant analysis(FDA) in AdaBoost, we further propose the recursive nonparametric discriminant analysis (RNDA) to handle more general cases. Those discriminant analysis features are not constrained with geometric shape and can provide better accuracy. The compact size of feature set allows to select a near optimal subset of features and construct the probabilistic classifiers by greedy searching. The proposed methods are applied to multi-view face and eye detection and achieve good accuracy.

关键词： Face detection Object detection computer vision pattern recognition Feature extraction Statistical learning Systems engineering and theory Eyes Shape Error analysis

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On the localization of straight lines in 3D space from single 2D images

On the localization of straight lines in 3D space from singl...

引用

conference on computer vision and pattern recognition (cvpr)

作者： V. Caglioti S. Gasparini Dipartimento di Elettronica e Informazione Politecnico di Milano Milan Italy

The reconstruction of 3D scenes constituted by straight lines can find many applications both in computer vision and in mobile robotics. Most of the approaches to this problem involve either stereo-vision or the analysis of a sequence of images taken from different viewpoints: in both cases, the solution of the correspondence problem is required. This paper studies the localization of straight lines in 3D space from single ID images, acquired by a catadioptric camera. In general, using a noncentral camera, the viewing rays starting from the points of a straight line constitute a non-planar surface: if this non-planar surface only contains one straight line, other than the viewing rays, then the straight line can univocally be localized. Some conditions for the univocal localization of straight lines are derived. A simple technique for the straight line localization is presented, and some preliminary experimental results are discussed.

关键词： Cameras Image reconstruction Layout Application software computer vision Mobile computing Mobile robots Orbital robotics Robot vision systems Image analysis

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