检索结果-内蒙古大学图书馆

Conference on computer vision and pattern recognition (CVPR)

作者： Ke Colin Zheng Sing Bing Kang Michael F. Cohen Richard Szeliski University of Washington Seattle WA USA Microsoft Research Limited Redmond WA USA

Representations for interactive photorealistic visualization of scenes range from compact 2D panoramas to data-intensive 4D light fields. In this paper, we propose a technique for creating a layered representation from a sparse set of images taken with a hand-held camera. This representation, which we call a layered depth panorama (LDP), allows the user to experience 3D by off-axis panning. It combines the compelling experience of panoramas with limited 3D navigation. Our choice of representation is motivated by ease of capture and compactness. We formulate the problem of constructing the LDP as the recovery of color and geometry in a multi-perspective cylindrical disparity space. We leverage a graph cut approach to sequentially determine the disparity and color of each layer using multi-view stereo. Geometry visible through the cracks at depth discontinuities in a frontmost layer is determined and assigned to layers behind the frontmost layer. All layers are then used to render novel panoramic views with parallax. We demonstrate our approach on a variety of complex outdoor and indoor scenes.

关键词： Layout Cameras Rendering (computer graphics) Geometry Image reconstruction Solid modeling Visualization Image storage Costs computer vision

来源：评论

学校读者我要写书评

暂无评论

Real-time Object Classification in Video Surveillance Based on Appearance Learning

Real-time Object Classification in Video Surveillance Based ...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Lun Zhang Stan Z. Li Xiaotong Yuan Shiming Xiang Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

Classifying moving objects to semantically meaningful categories is important for automatic visual surveillance. However, this is a challenging problem due to the factors related to the limited object size, large intra-class variations of objects in a same class owing to different viewing angles and lighting, and real-time performance requirement in real-world applications. This paper describes an appearance-based method to achieve real-time and robust objects classification in diverse camera viewing angles. A new descriptor, i.e., the multi-block local binary pattern (MB-LBP), is proposed to capture the large-scale structures in object appearances. Based on MB-LBP features, an adaBoost algorithm is introduced to select a subset of discriminative features as well as construct the strong two-class classifier. To deal with the non-metric feature value of MB-LBP features, a multi-branch regression tree is developed as the weak classifiers of the boosting. Finally, the error correcting output code (ECOC) is introduced to achieve robust multi-class classification performance. Experimental results show that our approach can achieve real-time and robust object classification in diverse scenes.

关键词： Video surveillance Cameras Robustness Vehicles Classification tree analysis Layout Object recognition Shape Large-scale systems Error correction codes

来源：评论

学校读者我要写书评

暂无评论

INSPECTION OF METALLIC STAMPED PARTS USING AN IMAGE FUSION TECHNIQUE

引用

IFAC Proceedings Volumes 2007年第3期40卷 177-182页

作者： Eusebio de la Fuente López Félix Miguel Trespaderne

This paper presents a machine vision system for on-line inspection of large stamped car parts. The vision system includes a CCD camera and an illumination device that permit to obtain two images of the same zone illuminated from two different directions. The acquired images are fused using an energy function in order to eliminate the spurious features originated by glints and shadows of the metallic surface. The defects, if they are present, remain in the fused image and can easily be pointed out.

关键词： computer vision visual pattern recognition quality control

来源：评论

学校读者我要写书评

暂无评论

Bilattice-based Logical Reasoning for Human Detection

Bilattice-based Logical Reasoning for Human Detection

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Vinay D. Shet Jan Neumann Visvanathan Ramesh Larry S. Davis Siemens Corporate Research Inc. Princeton NJ USA Computer Vision Laboratory University of Maryland College Park MD USA

The capacity to robustly detect humans in video is a critical component of automated visual surveillance systems. This paper describes a bilattice based logical reasoning approach that exploits contextual information and knowledge about interactions between humans, and augments it with the output of different low level detectors for human detection. Detections from low level parts-based detectors are treated as logical facts and used to reason explicitly about the presence or absence of humans in the scene. Positive and negative information from different sources, as well as uncertainties from detections and logical rules, are integrated within the bilattice framework. This approach also generates proofs or justifications for each hypothesis it proposes. These justifications (or lack thereof) are further employed by the system to explain and validate, or reject potential hypotheses. This allows the system to explicitly reason about complex interactions between humans and handle occlusions. These proofs are also available to the end user as an explanation of why the system thinks a particular hypothesis is actually a human. We employ a boosted cascade of gradient histograms based detector to detect individual body parts. We have applied this framework to analyze the presence of humans in static images from different datasets.

关键词： Humans Detectors Layout Geometry Educational institutions computer vision Robustness Surveillance Uncertainty Histograms

来源：评论

学校读者我要写书评

暂无评论

SVM Based Scheme for Thai and English Script Identification

SVM Based Scheme for Thai and English Script Identification

引用

International Conference on Document Analysis and recognition

作者： S. Chanda O.R. Terrades U. Pal Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India Computer Vision Center Universitat Authnòma de Barcelona Barcelona Spain

In some Thai documents, a single text line of a document page may contain both Thai and English scripts. For the optical character recognition (OCR) of such a document page it is better to identify, at first, Thai and English script portions and then to use individual OCR system of the respective scripts on these identified portions. In this paper, a SVM based method is proposed for identification of word-wise printed English and Thai scripts from a single line of a document page. Here, at first, the document is segmented into lines and then lines are segmented into character groups (words). In the proposed scheme, we identify the script of the individual character group combining different character features obtained from structural shape, profile, component overlapping information, topological properties, water reservoir concept etc. Based on the experiment on 6110 data we obtained 99.36% script identification accuracy from the proposed scheme.

关键词： Support vector machines Optical character recognition software Support vector machine classification computer vision Optical network units Structural shapes Water resources Reservoirs Neural networks pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Graph Cut Based Optimization for MRFs with Truncated Convex Priors

Graph Cut Based Optimization for MRFs with Truncated Convex ...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Olga Veksler University of Western Ontario London Canada

Optimization with graph cuts became very popular in recent years. Progress in problems such as stereo correspondence, image segmentation, etc., can be attributed, in part, to the development of efficient graph cut based optimization. Recent evaluation of optimization techniques shows that the popular expansion and swap graph cut algorithms perform extremely well for energies where the underlying MRF has the Potts prior, which corresponds to the assumption that the true labeling is piecewise constant. For more general priors, however, such as corresponding to piece-wise smoothness assumption, both swap and expansion algorithms do not perform as well. We develop several optimization algorithms for truncated convex priors, which imply piecewise smoothness assumption. Both expansion and swap algorithms are based on moves that give each pixel a choice of only two labels. Our insight is that to obtain a good approximation under piecewise smoothness assumption, a pixel should have a choice among more than two labels. We develop new "range" moves which act on a larger set of labels than the expansion and swap algorithms. We evaluate our method on problems of image restoration, in-painting, and stereo correspondence. Our results show that we are able to get more accurate answers, both in terms of the energy, which is the direct goal, and in terms of accuracy, which is an indirect, but more important goal.

关键词： Labeling Image segmentation Image restoration Stereo vision Performance evaluation Computational modeling Simulated annealing computer vision computer graphics Stereo image processing

来源：评论

学校读者我要写书评

暂无评论

Compositional Boosting for Computing Hierarchical Image Structures

Compositional Boosting for Computing Hierarchical Image Stru...

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Tian-Fu Wu Gui-Song Xia Song-Chun Zhu Lotus Hill Institute of Computer Vision and Information Science Ezhou China Statistics Department University of California Los Angeles CA USA

In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called "graphlets", are the most frequently occurring primitives, junctions and composite junctions in natural images, and are arranged in a 3-layer And-Or graph representation. In this hierarchic model, larger graphlets are decomposed (in And-nodes) into smaller graphlets in multiple alternative ways (at Or-nodes), and parts are shared and re-used between graphlets. Then we present a compositional boosting algorithm for computing the 17 graphlets categories collectively in the Bayesian framework. The algorithm runs recursively for each node A in the And-Or graph and iterates between two steps -bottom-up proposal and top-down validation. The bottom-up step includes two types of boosting methods, (i) Detecting instances of A (often in low resolutions) using Adaboosting method through a sequence of tests (weak classifiers) image feature, (ii) Proposing instances of A (often in high resolution) by binding existing children nodes of A through a sequence of compatibility tests on their attributes (e.g angles, relative size etc). The Adaboosting and binding methods generate a number of candidates for node A which are verified by a top-down process in a way similar to Data-Driven Markov Chain Monte Carlo [18]. Both the Adaboosting and binding methods are trained off-line for each graphlet category, and the compositional nature of the model means the algorithm is recursive and can be learned from a small training set. We apply this algorithm to a wide range of indoor and outdoor images with satisfactory results.

关键词： Boosting Testing Image edge detection Image resolution Image segmentation computer vision Image recognition Bayesian methods Proposals Inference algorithms

来源：评论

学校读者我要写书评

暂无评论

Fourier Methods for Nonparametric Image Registration

Fourier Methods for Nonparametric Image Registration

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Nathan D. Cahill J. Alison Noble David J. Hawkes Wolfson Medical Vision Laboratory University of Oxford Oxford UK Research and Innovation Carestream Health Inc. Rochester NY USA Centre for Medical Image Computing University College London London UK

Nonparametric image registration algorithms use deformation fields to define nonrigid transformations relating two images. Typically, these algorithms operate by successively solving linear systems of partial differential equations. These PDE systems arise by linearizing the Euler-Lagrange equations associated with the minimization of a functional defined to contain an image similarity term and a regularizer. Iterative linear system solvers can be used to solve the linear PDE systems, but they can be extremely slow. Some faster techniques based on Fourier methods, multigrid methods, and additive operator splitting, exist for solving the linear PDE systems for specific combinations of regularizers and boundary conditions. In this paper, we show that Fourier methods can be employed to quickly solve the linear PDE systems for every combination of standard regularizers (diffusion, curvature, elastic, and fluid) and boundary conditions (Dirichlet, Neumann, and periodic).

关键词： Image registration Boundary conditions Poisson equations Partial differential equations Biomedical imaging Iterative algorithms Linear systems Differential equations Force measurement Standards development

来源：评论

学校读者我要写书评

暂无评论

Spatio-Temporal Markov Random Field for Video Denoising

Spatio-Temporal Markov Random Field for Video Denoising

引用

Conference on computer vision and pattern recognition (CVPR)

作者： Jia Chen Chi-Keung Tang Vision and Graphics Group Hong Kong University of Science and Technology Hong Kong China

This paper presents a novel spatio-temporal Markov random field (MRF) for video denoising. Two main issues are addressed in this paper, namely, the estimation of noise model and the proper use of motion estimation in the denoising process. Unlike previous algorithms which estimate the level of noise, our method learns the full noise distribution nonparametrically which serves as the likelihood model in the MRF. Instead of using deterministic motion estimation to align pixels, we set up a temporal likelihood by combining a probabilistic motion field with the learned noise model. The prior of this MRF is modeled by piece-wise smoothness. The main advantage of the proposed spatio-temporal MRF is that it integrates spatial and temporal information adaptively into a statistical inference framework, where the posteriori is optimized using graph cuts with alpha expansion. We demonstrate the performance of the proposed approach on benchmark data sets and real videos to show the advantages of our algorithm compared with previous single frame and multi-frame algorithms.

关键词： Markov random fields Noise reduction Noise level Motion estimation Inference algorithms Filtering Motion compensation Image restoration Uncertainty Gaussian noise

来源：评论

学校读者我要写书评

暂无评论

lambda-Connectedness Determination for Image Segmentation

lambda-Connectedness Determination for Image Segmentation

引用

Applied Imagery pattern recognition Workshop (AIPR)

作者： Li Chen Department of Computer Science and Information Technology University of District of Columbia Washington D.C. DC USA

ISBN: (纸本)9781424431625

Image segmentation is to separate an image into distinct homogeneous regions belonging to different objects. It is an essential step in image analysis and computer vision. This paper compares some segmentation technologies and attempts to find an automated way to better determine the parameters for image segmentation, especially the connectivity value of lambda in lambda-connected segmentation. Based on the theories on the maximum entropy method and Otsu's minimum variance method, we propose:(1)maximum entropy connectedness determination: a method that uses maximum entropy to determine the best lambda value in lambda-connected segmentation, and (2) minimum variance connectedness determination: a method that uses the principle of minimum variance to determine lambda value. Applying these optimization techniques in real images, the experimental results have shown great promise in the development of the new methods. In the end, we extend the above method to more general case in order to compare it with the famous Mumford-Shah method that uses variational principle and geometric measure.

关键词： Image segmentation Entropy Fuzzy sets computer vision Optimization methods Data mining Image edge detection pattern recognition computer science Information technology

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：