检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

1,535 篇 会议
21 册 图书
13 篇 期刊文献

馆藏范围

1,569 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,449 篇 工学
- 1,046 篇 计算机科学与技术...
- 655 篇 机械工程
- 358 篇 电气工程
- 111 篇 软件工程
- 55 篇 控制科学与工程
- 49 篇 信息与通信工程
- 35 篇 光学工程
- 28 篇 仪器科学与技术
- 17 篇 网络空间安全
- 15 篇 生物工程
- 9 篇 生物医学工程（可授...
- 8 篇 电子科学与技术（可...
- 8 篇 安全科学与工程
- 7 篇 测绘科学与技术
- 4 篇 化学工程与技术
- 3 篇 建筑学
112 篇 医学
- 108 篇 临床医学
- 6 篇 基础医学(可授医学...
- 4 篇 特种医学
87 篇 理学
- 38 篇 物理学
- 34 篇 数学
- 24 篇 生物学
- 12 篇 统计学（可授理学、...
- 9 篇 系统科学
- 5 篇 化学
42 篇 管理学
- 32 篇 图书情报与档案管...
- 10 篇 管理科学与工程(可...
24 篇 艺术学
- 24 篇 设计学（可授艺术学...
19 篇 法学
- 19 篇 社会学
15 篇 文学
- 15 篇 新闻传播学
2 篇 教育学
2 篇 农学
1 篇 经济学

主题

528 篇 computer vision
139 篇 face recognition
135 篇 pattern recognit...
135 篇 feature extracti...
130 篇 cameras
129 篇 image segmentati...
128 篇 object recogniti...
115 篇 object detection
103 篇 training
98 篇 robustness
94 篇 images
92 篇 image recognitio...
90 篇 shape
90 篇 layout
84 篇 visualization
77 篇 image reconstruc...
76 篇 humans
70 篇 computer science
66 篇 computational mo...
66 篇 image classifica...

机构

23 篇 rhein westfal th...
18 篇 carnegie mellon ...
16 篇 chinese acad sci...
15 篇 stanford univ st...
14 篇 univ chinese aca...
11 篇 australian natl ...
11 篇 univ calif berke...
10 篇 univ sci & techn...
10 篇 mit cambridge ma...
10 篇 univ maryland co...
9 篇 microsoft res as...
9 篇 univ washington ...
8 篇 microsoft resear...
8 篇 microsoft res re...
8 篇 natl univ singap...
7 篇 chinese univ hon...
7 篇 tech univ munich...
6 篇 mpi intelligent ...
6 篇 kaust thuwal
6 篇 imperial coll lo...

作者

20 篇 leibe bastian
12 篇 ji qiang
10 篇 li stan z.
9 篇 pal umapada
8 篇 zhang lei
8 篇 chellappa rama
8 篇 lei zhen
8 篇 zafeiriou stefan...
8 篇 hu weiming
8 篇 hua gang
7 篇 ramanan deva
7 篇 wang xiaogang
7 篇 yan shuicheng
7 篇 mubarak shah
6 篇 van gool luc
6 篇 darrell trevor
6 篇 luiten jonathon
6 篇 pollefeys marc
6 篇 bischof horst
6 篇 ghanem bernard

语言

1,554 篇 英文
9 篇 土耳其文
2 篇 日文
2 篇 其他
1 篇 西班牙文
1 篇 中文

检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR"

共 1569 条记录，以下是1361-1370 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Pair-Activity Classification by Bi-Trajectories Analysis

Pair-Activity Classification by Bi-Trajectories Analysis

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.12

作者： Yue Zhou Shuicheng Yan thomas S. Huang Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign USA Department of Electrical and Computer Engineering National University of Singapore Singapore

In this paper, we address the pair-activity classification problem, which explores the relationship between two active objects based on their motion information. Our contributions are three-fold. First, we design a set of features, e.g., causality ratio and feedback ratio based on the Granger Causality Test (GCT), for describing the pair-activities encoded as trajectory pairs. these features along with conventional velocity and position features are essentially of multi-modalities, and may be greatly different in scale and importance. To make full use of them, we then present a novel feature normalization procedure to learn the coefficients for weighting these features by maximizing the discriminating power measured by weighted correlation. Finally, we collected a pair-activity database of five categories, each of which consists of about 170 instances. the extensive experiments on this database validate the effectiveness of the designed features for pair-activity representation, and also demonstrate that the proposed feature normalization procedure greatly boosts the pair-activity classification accuracy.

关键词： Information analysis Feedback Testing Spatial databases computer vision Trajectory Motion analysis Power measurement Weight measurement Event detection

来源：评论

学校读者我要写书评

暂无评论

Annotating Collections of Photos Using Hierarchical Event and Scene Models

Annotating Collections of Photos Using Hierarchical Event an...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.1

作者： Liangliang Cao Jiebo Luo Henry Kautz thomas S. Huang Department of Electrical and Computer Engineering University of Illinois USA Kodak Research Laboratories Eastman Kodak (Japan) Limited USA

Most image annotation systems consider a single photo at a time and label photos individually. In this work, we focus on collections of personal photos and explore the associated GPS and time information for semantic annotation. First, we employ a constrained clustering method to partition a photo collection into event-based sub-collections, considering that the GPS records may be partly missing (a practical issue). We then use conditional random field (CRF) models to exploit the correlation between photos based on (1) time-location constraints and (2) the relationship between collection-level annotation (i.e., events) and image-level annotation (i.e., scenes). With the introduction of such a multi-level annotation hierarchy, our system addresses the problem of annotating consumer photo collections that requires a more hierarchical description of the customers' activities than do the simpler image annotation tasks. the efficacy of the proposed system is validated using a geotagged customer photo collection database, which consists of over 100 folders and is labeled for 12 events and 12 scenes.

关键词： Layout Global Positioning System computer vision Information resources Cameras Laboratories Clustering methods Image databases Image retrieval Event detection

来源：评论

学校读者我要写书评

暂无评论

Kernel-based learning of cast shadows from a physical model of light sources and surfaces for low-level segmentation

Kernel-based learning of cast shadows from a physical model ...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.3

作者： Nicolas Martel-Brisson Andre Zaccarin Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Laval University QUE Canada

In background subtraction, cast shadows induce silhouette distortions and object fusions hindering performance of high level algorithms in scene monitoring. We introduce a nonparametric framework to model surface behavior when shadows are cast on them. Based on physical properties of light sources and surfaces, we identify a direction in RGB space on which background surface values under cast shadows are found. We then model the posterior distribution of lighting attenuation under cast shadows and foreground objects, which allows differentiation of foreground and cast shadow values with similar chromaticity. the algorithms are completely unsupervised and take advantage of scene activity to learn model parameters. Spatial gradient information is also used to reinforce the learning process. Contributions are two-fold. Firstly, with a better model describing cast shadows on surfaces, we achieve a higher success rate in segmenting moving cast shadows in complex scenes. Secondly, obtaining such models is a step toward a full scene parametrization where light source properties, surface reflectance models and scene 3D geometry are estimated for low-level segmentation.

关键词： Light sources Layout Solid modeling Geometry Lighting Reflectivity Object recognition Video sequences Attenuation computer vision

来源：评论

学校读者我要写书评

暂无评论

Scene Classification with Low-dimensional Semantic Spaces and Weak Supervision

Scene Classification with Low-dimensional Semantic Spaces an...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.1

作者： Nikhil Rasiwasia Nuno Vasconcelos Department of Electrical and Computer Engineering University of California San Diego USA

A novel approach to scene categorization is proposed. Similar to previous works of [11, 15, 3, 12], we introduce an intermediate space, based on a low dimensional semantic "theme" image representation. However, instead of learning the themes in an unsupervised manner, they are learned with weak supervision, from casual image annotations. Each theme induces a probability density on the space of low-level features, and images are represented as vectors of posterior theme probabilities. this enables an image to be associated with multiple themes, even when there are no multiple associations in the training labels. An implementation is presented and compared to various existing algorithms, on benchmark datasets. It is shown that the proposed low dimensional representation correlates well with human scene understanding, and is able to learn theme co-occurrences without explicit training. It is also shown to outperform unsupervised latent-space methods, with much smaller training complexity, and to achieve performance close to the state of the art methods, which rely on much higher-dimensional image representations. Finally a study of the effect of dimensionality on the classification performance is presented, indicating that the dimensionality of theme space grows sub-linearly with the number of scene categories.

关键词： Layout Image representation Humans computer vision Robustness Support vector machines Object detection Cities and towns Frequency Large-scale systems

来源：评论

学校读者我要写书评

暂无评论

Efficient Mean Shift Belief Propagation for vision Tracking

Efficient Mean Shift Belief Propagation for Vision Tracking

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.4

作者： Minwoo Park Yanxi Liu Robert T. Collins Department of Computer Science and Engineering Pennsylvania State University University Park PA USA Department of Electrical Engineering Pennsylvania State University University Park PA USA

A mechanism for efficient mean-shift belief propagation (MSBP) is introduced. the novelty of our work is to use mean-shift to perform nonparametric mode-seeking on belief surfaces generated within the belief propagation framework. Belief Propagation (BP) is a powerful solution for performing inference in graphical models. However, there is a quadratic increase in the cost of computation with respect to the size of the hidden variable space. While the recently proposed nonparametric belief propagation (NBP) has better performance in terms of speed, even for continuous hidden variable spaces, computation is still slow due to the particle filter sampling process. Our MSBP method only needs to compute a local grid of samples of the belief surface during each iteration. this approach needs a significantly smaller number of samples than NBP, reducing computation time, yet it also yields more accurate and stable solutions. the efficiency and robustness of MSBP is compared against other variants of BP on applications in multi-target tracking and 2D articulated body tracking.

关键词： Belief propagation Graphical models Robustness Spatial resolution Lattices computer science Computational efficiency Particle filters Sampling methods Grid computing

来源：评论

学校读者我要写书评

暂无评论

Taylor Expansion Based Classifier Adaptation: Application to Person Detection

Taylor Expansion Based Classifier Adaptation: Application to...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.11

作者： Cha Zhang Raffay Hamid Zhengyou Zhang Microsoft Research Redmond WA Georgia Institute of Technology Atlanta GA Microsoft Research Redmond WA USA

Because of the large variation across different environments, a generic classifier trained on extensive data-sets may perform sub-optimally in a particular test environment. In this paper, we present a general framework for classifier adaptation, which improves an existing generic classifier in the new test environment. Viewing classifier learning as a cost minimization problem, we perform classifier adaptation by combining the cost function on the old data-sets with the cost function on the data-set collected from the new environment. the former term is further approximated with its second order Taylor expansion to reduce the amount of information that needs to be saved for adaptation. Unlike traditional approaches that are often designed for a specific application or classifier, our scheme is applicable to various types of classifiers and user labels. We demonstrate this property on two popular classifiers (logistic regression and boosting), while using two types of user labels (direct labels and similarity labels). Extensive experiments conducted for the task of person detection in conference-room environments show that significant performance improvement can be achieved with our proposed method.

关键词： Taylor series Testing Detectors Cost function Handwriting recognition Speech recognition Performance evaluation Boosting Face detection Object detection

来源：评论

学校读者我要写书评

暂无评论

Online Learning of Patch Perspective Rectification for Efficient Object Detection

Online Learning of Patch Perspective Rectification for Effic...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.5

作者： Stefan Hinterstoisser Selim Benhimane Nassir Navab Pascal Fua Vincent Lepetit Department of Computer Science Technical University Munich Garching Germany Computer Vision Laboratory École Polytechnique Fédérale de Lausanne Lausanne Switzerland

For a large class of applications, there is time to train the system. In this paper, we propose a learning-based approach to patch perspective rectification, and show that it is both faster and more reliable than state-of-the-art ad hoc affine region detection methods. Our method performs in three steps. First, a classifier provides for every keypoint not only its identity, but also a first estimate of its transformation. this estimate allows carrying out, in the second step, an accurate perspective rectification using linear predictors. We show that both the classifier and the linear predictors can be trained online, which makes the approach convenient. the last step is a fast verification -made possible by the accurate perspective rectification- of the patch identity and its sub-pixel precision position estimation. We test our approach on real-time 3D object detection and tracking applications. We show that we can use the estimated perspective rectifications to determine the object pose and as a result, we need much fewer correspondences to obtain a precise pose estimation.

关键词： Object detection Detectors Robustness Image recognition computer science computer vision Laboratories Application software Testing Databases

来源：评论

学校读者我要写书评

暂无评论

Distributed Data Association and Filtering for Multiple Target Tracking

Distributed Data Association and Filtering for Multiple Targ...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.6

作者： Ting Yu Ying Wu Nils O. Krahnstoever Peter H. Tu GE Global Research Visualization and Computer Vision Laboratory Niskayuna NY USA Department of Electrical Engineering and Computer Sciences Northwestern University Evanston IL USA

this paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackers' motion and association variables is adopted. Considering the interleaved nature of data association and tracker filtering, the multi-target tracking is formulated as a missing data problem, and the solution is found by the proposed variational EM algorithm. We analytically show that 1) the posteriori distributions of trackers' motions (the real interests in terms of tracking applications) can be effectively computed in the E-step of the EM iterations, and 2) the solution of trackers' association variables can be pursued under a derived graph-based discrete optimization formulation, thus efficiently estimated in the M-step by the recently emerging graph optimization algorithms. the proposed approach is very general such that sophisticated data association priori and likelihood function can be easily incorporated. this general framework is tested with both simulation data and real world surveillance video. the reported qualitative and quantitative studies verify the effectiveness and low computational cost of the algorithm.

关键词： Target tracking Distributed computing Filtering algorithms Algorithm design and analysis Motion analysis Motion estimation Testing Computational modeling Surveillance Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Image De-fencing

Image De-fencing

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.4

作者： Yanxi Liu Tamara Belkina James H. Hays Roberto Lublinerman Department of Electrical Engineering The Pennsylvania State University USA Department of Computer Science and Engineering Computer Science Department Carnegie Mellon University USA Department of Computer Science and Engineering Pennsylvania State University USA

We introduce a novel image segmentation algorithm that uses translational symmetry as the primary foreground/background separation cue. We investigate the process of identifying and analyzing image regions that present approximate translational symmetry for the purpose of image fourground/background separation. In conjunction with texture-based inpainting, understanding the different see-through layers allows us to perform powerful image manipulations such as recovering a mesh-occluded background (as much as 53% occluded area) to achieve the effect of image and photo de-fencing. Our algorithm consists of three distinct phases-^s(1) automatically finding the skeleton structure of a potential frontal layer (fence) in the form of a deformed lattice, (2) separating foreground/background layers using appearance regularity, and (3) occluded foreground inpainting to reveal a complete, non-occluded image. Each of these three tasks presents its own special computational challenges that are not encountered in previous, general image de-layering or texture inpainting applications.

关键词： Image segmentation Lattices computer science Skeleton Topology Layout Image analysis Airports computer applications Digital images

来源：评论

学校读者我要写书评

暂无评论

Face Shape Recovery from a Single Image Using CCA Mapping between Tensor Spaces

Face Shape Recovery from a Single Image Using CCA Mapping be...

引用

26th ieee conference on computer vision and pattern recognition (cvpr 2008), vol.1

作者： Zhen Lei Qinqun Bai Ran He Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China

In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor space to 3D tensor space, learned by using statistical learning, is used for the shape recovery. In the learning phase, the two tensor models are constructed for NIR and 3D images respectively, and a canonical correlation analysis (CCA) based multi-variate mapping from NIR to 3D faces is learned from a given training set of NIR-3D face pairs. In the reconstruction phase, given an NIR face image, the depth map is computed directly using the learned mapping with the help of tensor models. Experimental results are provided to evaluate the accuracy and speed of the method. the work provides a practical solution for reliable and fast shape recovery and modeling of 3D objects.

关键词： Shape Tensile stress Image reconstruction Humans Surface reconstruction Face detection Surface fitting Magnetic force microscopy Lighting Infrared imaging

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共157页 << < 133 134 135 136 137 138 139 140 141 142 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：