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971-980 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：

Fixation and Saccade based Face recognition from Single Image per Person with Various Occlusions and Expressions

Fixation and Saccade based Face Recognition from Single Imag...

引用

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

作者： Wei, Xingjie Li, Chang-Tsun Univ Warwick Dept Comp Sci Coventry CV4 7AL W Midlands England

ISBN: (纸本)9780769549903

Face recognition technique is widely used in the real-world applications over the past decade. Different from other biometric traits such as fingerprint and iris, face is the biological nature for humans to recognise a person even met just once. In this paper, we propose a novel method, which simulates the mechanism of fixations and saccades in human visual perception, to handle the face recognition from single image per person problem. Our method is robust to the local deformations of the face (i.e., expression changes and occlusions). Especially for the occlusion related problems, which have not received enough attentions compared with other challenging variations of illumination, expression and pose, our method significantly outperforms the state-of-the-art approaches despite various types of occlusions. Experimental results on the FRGC and the AR databases confirm the effectiveness of our method.

关键词： computer graphics face recognition

来源：评论

学校读者我要写书评

暂无评论

Pixel-level Hand Detection in Ego-Centric Videos

Pixel-level Hand Detection in Ego-Centric Videos

引用

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

作者： Li, Cheng Kitani, Kris M. Tsinghua Univ Beijing 100084 Peoples R China Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9780769549897

We address the task of pixel-level hand detection in the context of ego-centric cameras. Extracting hand regions in ego-centric videos is a critical step for understanding hand-object manipulation and analyzing hand-eye coordination. However, in contrast to traditional applications of hand detection, such as gesture interfaces or sign-language recognition, ego-centric videos present new challenges such as rapid changes in illuminations, significant camera motion and complex hand-object manipulations. To quantify the challenges and performance in this new domain, we present a fully labeled indoor/outdoor ego-centric hand detection benchmark dataset containing over 200 million labeled pixels, which contains hand images taken under various illumination conditions. Using both our dataset and a publicly available ego-centric indoors dataset, we give extensive analysis of detection performance using a wide range of local appearance features. Our analysis highlights the effectiveness of sparse features and the importance of modeling global illumination. We propose a modeling strategy based on our findings and show that our model outperforms several baseline approaches.

关键词： feature extraction image motion analysis image resolution image sensors lighting object detection sign language recognition video signal processing

来源：评论

学校读者我要写书评

暂无评论

Anti-spoofing in action: joint operation with a verification system

Anti-spoofing in action: joint operation with a verification...

引用

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

作者： Chingovska, Ivana Anjos, Andre Marcel, Sebastien Idiap Res Inst CH-1920 Martigny Switzerland

ISBN: (纸本)9780769549903

Besides the recognition task, today's biometric systems need to cope with additional problem: spoofing attacks. Up to date, academic research considers spoofing as a binary classification problem: systems are trained to discriminate between real accesses and attacks. However, spoofing counter-measures are not designated to operate stand-alone, but as a part of a recognition system they will protect. In this paper, we study techniques for decision-level and score-level fusion to integrate a recognition and anti-spoofing systems, using an open-source framework that handles the ternary classification problem (clients, impostors and attacks) transparently. By doing so, we are able to report the impact of different spoofing counter-measures, fusion techniques and thresholding on the overall performance of the final recognition system. For a specific use-case covering face verification, experiments show to what extent simple fusion improves the trustworthiness of the system when exposed to spoofing attacks.

关键词： biometrics (access control) face recognition image classification security of data sensor fusion

来源：评论

学校读者我要写书评

暂无评论

Multi-target Tracking by Rank-1 Tensor Approximation

Multi-target Tracking by Rank-1 Tensor Approximation

引用

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

作者： Shi, Xinchu Ling, Haibin Xing, Junliang Hu, Weiming Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China Temple Univ Dept Comp & Informat Sci Philadelphia PA 19122 USA

ISBN: (纸本)9780769549897

In this paper we formulate multi-target tracking (MTT) as a rank-1 tensor approximation problem and propose an l(1) norm tensor power iteration solution. In particular, a high order tensor is constructed based on trajectories in the time window, with each tensor element as the affinity of the corresponding trajectory candidate. the local assignment variables are the l(1) normalized vectors, which are used to approximate the rank-1 tensor. Our approach provides a flexible and effective formulation where both pairwise and high-order association energies can be used expediently. We also show the close relation between our formulation and the multi-dimensional assignment (MDA) model. To solve the optimization in the rank-1 tensor approximation, we propose an algorithm that iteratively powers the intermediate solution followed by an l(1) normalization. Aside from effectively capturing high-order motion information, the proposed solver runs efficiently with proved convergence. the experimental validations are conducted on two challenging datasets and our method demonstrates promising performances on both.

关键词： approximation theory computer vision human computer interaction iterative methods target tracking tensors vectors

来源：评论

学校读者我要写书评

暂无评论

Learning to Detect Partially Overlapping Instances

Learning to Detect Partially Overlapping Instances

引用

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

作者： Arteta, Carlos Lempitsky, Victor Noble, J. Alison Zisserman, Andrew Univ Oxford Dept Engn Sci Oxford OX1 2JD England Skolkovo Inst Sci & Technol Moskovsky Russia

ISBN: (纸本)9780769549897

the objective of this work is to detect all instances of a class (such as cells or people) in an image. the instances may be partially overlapping and clustered, and hence quite challenging for traditional detectors, which aim at localizing individual instances. Our approach is to propose a set of candidate regions, and then select regions based on optimizing a global classification score, subject to the constraint that the selected regions are non-overlapping. Our novel contribution is to extend standard object detection by introducing separate classes for tuples of objects into the detection process. For example, our detector can pick a region containing two or three object instances, while assigning such region an appropriate label. We show that this formulation can be learned within the structured output SVM framework, and that the inference in such model can be accomplished using dynamic programming on a tree structured region graph. Furthermore, the learning only requires weak annotations - a dot on each instance. the improvement resulting from the addition of the capability to detect tuples of objects is demonstrated on quite disparate data sets: fluorescence microscopy images and UCSD pedestrians.

关键词： dynamic programming image classification inference mechanisms object detection pattern clustering support vector machines trees (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Explicit Occlusion Modeling for 3D Object Class Representations

Explicit Occlusion Modeling for 3D Object Class Representati...

引用

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

作者： Zia, M. Zeeshan Stark, Michael Schindler, Konrad Swiss Fed Inst Technol Photogrammetry & Remote Sensing Zurich Switzerland Stanford Univ Stanford CA 94305 USA Max Planck Inst Informat Saarbrucken Germany

ISBN: (纸本)9780769549897

Despite the success of current state-of-the-art object class detectors, severe occlusion remains a major challenge. this is particularly true for more geometrically expressive 3D object class representations. While these representations have attracted renewed interest for precise object pose estimation, the focus has mostly been on rather clean datasets, where occlusion is not an issue. In this paper, we tackle the challenge of modeling occlusion in the context of a 3D geometric object class model that is capable of fine-grained, part-level 3D object reconstruction. Following the intuition that 3D modeling should facilitate occlusion reasoning, we design an explicit representation of likely geometric occlusion patterns. Robustness is achieved by pooling image evidence from of a set of fixed part detectors as well as a non-parametric representation of part configurations in the spirit of poselets. We confirm the potential of our method on cars in a newly collected data set of inner-city street scenes with varying levels of occlusion, and demonstrate superior performance in occlusion estimation and part localization, compared to baselines that are unaware of occlusions.

关键词： computer graphics image reconstruction image representation object detection pose estimation

来源：评论

学校读者我要写书评

暂无评论

Weakly-Supervised Dual Clustering for Image Semantic Segmentation

Weakly-Supervised Dual Clustering for Image Semantic Segment...

引用

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

作者： Liu, Yang Liu, Jing Li, Zechao Tang, Jinhui Lu, Hanqing Chinese Acad Sci Inst Automat NLPR Beijing 100190 Peoples R China Nanjing Univ Sci & Tech Sch Comp Sci Beijing 210044 Peoples R China

ISBN: (纸本)9780769549897

In this paper, we propose a novel Weakly-Supervised Dual Clustering (WSDC) approach for image semantic segmentation with image-level labels, i.e., collaboratively performing image segmentation and tag alignment with those regions. the proposed approach is motivated from the observation that superpixels belonging to an object class usually exist across multiple images and hence can be gathered via the idea of clustering. In WSDC, spectral clustering is adopted to cluster the superpixels obtained from a set of over-segmented images. At the same time, a linear transformation between features and labels as a kind of discriminative clustering is learned to select the discriminative features among different classes. the both clustering outputs should be consistent as much as possible. Besides, weakly-supervised constraints from image-level labels are imposed to restrict the labeling of superpixels. Finally, the non-convex and non-smooth objective function are efficiently optimized using an iterative CCCP procedure. Extensive experiments conducted on MSRC and LabelMe datasets demonstrate the encouraging performance of our method in comparison with some state-of-the-arts.

关键词： image segmentation pattern clustering

来源：评论

学校读者我要写书评

暂无评论

Cumulative Attribute Space for Age and Crowd Density Estimation

Cumulative Attribute Space for Age and Crowd Density Estimat...

引用

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

作者： Chen, Ke Gong, Shaogang Xiang, Tao Loy, Chen Change Univ London London E1 4NS England Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9780769549897

A number of computer vision problems such as human age estimation, crowd density estimation and body/face pose (view angle) estimation can be formulated as a regression problem by learning a mapping function between a high dimensional vector-formed feature input and a scalar-valued output. Such a learning problem is made difficult due to sparse and imbalanced training data and large feature variations caused by both uncertain viewing conditions and intrinsic ambiguities between observable visual features and the scalar values to be estimated. Encouraged by the recent success in using attributes for solving classification problems with sparse training data, this paper introduces a novel cumulative attribute concept for learning a regression model when only sparse and imbalanced data are available. More precisely, low-level visual features extracted from sparse and imbalanced image samples are mapped onto a cumulative attribute space where each dimension has clearly defined semantic interpretation (a label) that captures how the scalar output value (e. g. age, people count) changes continuously and cumulatively. Extensive experiments show that our cumulative attribute framework gains notable advantage on accuracy for both age estimation and crowd counting when compared against conventional regression models, especially when the labelled training data is sparse with imbalanced sampling.

关键词： computer vision feature extraction image classification learning (artificial intelligence) pose estimation regression analysis

来源：评论

学校读者我要写书评

暂无评论

Exemplar-Based Face Parsing

Exemplar-Based Face Parsing

引用

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

作者： Smith, Brandon M. Zhang, Li Brandt, Jonathan Lin, Zhe Yang, Jianchao Univ Wisconsin Madison Madison WI 53706 USA Adobe Res Madison WI 53706 USA

ISBN: (纸本)9780769549897

In this work, we propose an exemplar-based face image segmentation algorithm. We take inspiration from previous works on image parsing for general scenes. Our approach assumes a database of exemplar face images, each of which is associated with a hand-labeled segmentation map. Given a test image, our algorithm first selects a subset of exemplar images from the database, Our algorithm then computes a non-rigid warp for each exemplar image to align it with the test image. Finally, we propagate labels from the exemplar images to the test image in a pixel-wise manner, using trained weights to modulate and combine label maps from different exemplars. We evaluate our method on two challenging datasets and compare with two face parsing algorithms and a general scene parsing algorithm. We also compare our segmentation results with contour-based face alignment results;that is, we first run the alignment algorithms to extract contour points and then derive segments from the contours. Our algorithm compares favorably with all previous works on all datasets evaluated.

关键词： face recognition feature extraction image resolution image segmentation

来源：评论

学校读者我要写书评

暂无评论

Collective Activity Detection using Hinge-loss Markov Random Fields

Collective Activity Detection using Hinge-loss Markov Random...

引用

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

作者： London, Ben Khamis, Sameh Bach, Stephen H. Huang, Bert Getoor, Lise Davis, Larry Univ Maryland College Pk MD 20742 USA

ISBN: (纸本)9780769549903

We propose hinge-loss Markov random fields (HL-MRFs), a powerful class of continuous-valued graphical models, for high-level computer vision tasks. HL-MRFs are characterized by log-concave density functions, and are able to perform efficient, exact inference. their templated hinge-loss potential functions naturally encode soft-valued logical rules. Using the declarative modeling language probabilistic soft logic, one can easily define HL-MRFs via familiar constructs from first-order logic. We apply HL-MRFs to the task of activity detection, using principles of collective classification. Our model is simple, intuitive and interpretable. We evaluate our model on two datasets and show that it achieves significant lift over the low-level detectors.

关键词： Markov processes computer vision image classification object detection probabilistic logic random processes

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 << < 94 95 96 97 98 99 100 101 102 103 > >>

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：