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

54 篇 会议
3 篇 期刊文献
1 册 图书

馆藏范围

58 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

21 篇 工学
- 11 篇 机械工程
- 9 篇 仪器科学与技术
- 8 篇 计算机科学与技术...
- 8 篇 软件工程
- 5 篇 控制科学与工程
- 4 篇 光学工程
- 3 篇 信息与通信工程
- 1 篇 建筑学
- 1 篇 土木工程
- 1 篇 生物工程
8 篇 理学
- 4 篇 数学
- 4 篇 物理学
- 2 篇 统计学（可授理学、...
- 1 篇 生物学
- 1 篇 系统科学
4 篇 管理学
- 2 篇 管理科学与工程(可...
- 2 篇 图书情报与档案管...
- 1 篇 工商管理
1 篇 法学
- 1 篇 社会学

主题

19 篇 computer vision
13 篇 humans
11 篇 object recogniti...
10 篇 robots
9 篇 cameras
9 篇 laboratories
9 篇 shape
9 篇 robustness
8 篇 grasping
7 篇 image segmentati...
7 篇 pattern recognit...
7 篇 robot sensing sy...
6 篇 computer science
6 篇 support vector m...
6 篇 machine vision
6 篇 robot vision sys...
5 篇 numerical analys...
5 篇 histograms
5 篇 layout
4 篇 object detection

机构

7 篇 computer vision ...
3 篇 computer vision ...
3 篇 computational vi...
2 篇 computer vision ...
2 篇 centre for auton...
2 篇 computer vision ...
2 篇 computer vision ...
1 篇 department of co...
1 篇 computational vi...
1 篇 computational vi...
1 篇 autonomous motio...
1 篇 multimodal inter...
1 篇 department of nu...
1 篇 laboratory of ro...
1 篇 humanoids and in...
1 篇 computer vision ...
1 篇 automation and c...
1 篇 department of co...
1 篇 institute for an...
1 篇 laboratory of ro...

作者

20 篇 danica kragic
4 篇 omid aghazadeh
4 篇 t. lindeberg
4 篇 b. caputo
4 篇 carl henrik ek
4 篇 dan song
4 篇 d. kragic
3 篇 javier romero
3 篇 stefan carlsson
3 篇 kragic danica
3 篇 kai huebner
3 篇 marianna madry
3 篇 josephine sulliv...
3 篇 i. laptev
3 篇 hedvig kjellströ...
3 篇 renaud detry
3 篇 jeannette bohg
2 篇 tamim asfour
2 篇 d. roobaert
2 篇 tsotsos john

语言

58 篇 英文

检索条件"机构=Computer Vision and Active Perception Laboratory"

共 58 条记录，以下是11-20 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：

Combining central and peripheral vision for reactive robot navigation

Combining central and peripheral vision for reactive robot n...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： A.A. Argyros F. Bergholm Computer Vision and Robotics Laboratory ICS/FORTH Crete Greece Computational Vision and Active Perception Laboratory Stockholm Sweden

In this paper we present a new method for vision-based, reactive robot navigation that enables a robot to move in the middle of the free space by exploiting both central and peripheral vision. The robot employs a forward-looking camera for central vision and two side-looking cameras for sensing the periphery of its visual field. The developed method combines the information acquired by this trinocular vision system and produces low-level motor commands that keep the robot in the middle of the free space. The approach follows the purposive vision paradigm in the sense that vision is not studied in isolation but in the context of the behaviors that the system is engaged as well as the environment and the robot's motor capabilities. It is demonstrated that by taking into account these issues, vision processing can be drastically simplified still giving rise to quite complex behaviors. The proposed method does not make strict assumptions about the environment, requires very low level information to be extracted from the images, produces a robust robot behavior and is computationally efficient. Results obtained by bath simulations and from a prototype on-line implementation demonstrate the effectiveness of the method.

关键词： Robot vision systems Robot sensing systems Orbital robotics Cameras Navigation Machine vision Data mining Robustness Computational modeling Virtual prototyping

来源：评论

学校读者我要写书评

暂无评论

Minimum volume bounding box decomposition for shape approximation in robot grasping

Minimum volume bounding box decomposition for shape approxim...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Kai Huebner Steffen Ruthotto Danica Kragic Members of the Computer Vision & Active Perception Laboratory Kth Royal Institute of Technology Stockholm Sweden

Thinking about intelligent robots involves consideration of how such systems can be enabled to perceive, interpret and act in arbitrary and dynamic environments. While sensor perception and model interpretation focus on the robot's internal representation of the world rather passively, robot grasping capabilities are needed to actively execute tasks, modify scenarios and thereby reach versatile goals. These capabilities should also include the generation of stable grasps to safely handle even objects unknown to the robot. We believe that the key to this ability is not to select a good grasp depending on the identification of an object (e.g. as a cup), but on its shape (e.g. as a composition of shape primitives). In this paper, we envelop given 3D data points into primitive box shapes by a fit-and-split algorithm that is based on an efficient Minimum Volume Bounding Box implementation. Though box shapes are not able to approximate arbitrary data in a precise manner, they give efficient clues for planning grasps on arbitrary objects. We present the algorithm and experiments using the 3D grasping simulator Grasplt!.

关键词： Shape Robot sensing systems Intelligent robots Robotics and automation Grasping Clouds Service robots USA Councils Intelligent sensors Kinematics

来源：评论

学校读者我要写书评

暂无评论

Response Binning: Improved Weak Classifiers for Boosting

Response Binning: Improved Weak Classifiers for Boosting

引用

IEEE Symposium on Intelligent Vehicle

作者： B. Rasolzadeh L. Petersson N. Pettersson Computer Vision and Active Perception Laboratory Royal Institute of Technology Stockholm Sweden NICTA Canberra Australia

This paper demonstrates the value of improving the discriminating strength of weak classifiers in the context of boosting by using response binning. The reasoning is centered around, but not limited to, the well known Haar-features used by Viola and Jones (2001) in their face detection/pedestrian detection systems. It is shown that using a weak classifier based on a single threshold is sub-optimal and in the case of the Haar-feature inadequate. A more general method for features with multi-modal responses is derived that is easily used in boosting mechanisms that accepts a confidence measure, such as the RealBoost algorithm. The method is evaluated by boosting a single stage classifier and compare the performance to previous approaches

关键词： Boosting Face detection Australia Intelligent vehicles computer vision Filters Performance analysis Algorithm design and analysis Pattern recognition Automobiles

来源：评论

学校读者我要写书评

暂无评论

Object recognition using composed receptive field histograms of higher dimensionality

Object recognition using composed receptive field histograms...

引用

International Conference on Pattern Recognition

作者： O. Linde T. Lindeberg Department of Numerical Analysis and Computer Science KTH Computational Vision and Active Perception Laboratory Stockholm Sweden

Effective methods for recognising objects or spatio-temporal events can be constructed based on receptive field responses summarised into histograms or other histogram-like image descriptors. This work presents a set of composed histogram features of higher dimensionality, which give significantly better recognition performance compared to the histogram descriptors of lower dimensionality that were used in the original papers by Swain & Bollard (1991) or Schiele & Crowley (2000). The use of histograms of higher dimensionality is made possible by a sparse representation for efficient computation and handling of higher-dimensional histograms. Results of extensive experiments are reported, showing how the performance of histogram-based recognition schemes depend upon different combinations of cues, in terms of Gaussian derivatives or differential invariants applied to either intensity information, chromatic information or both. It is shown that there exist composed higher-dimensional histogram descriptors with much better performance for recognising known objects than previously used histogram features. Experiments are also reported of classifying unknown objects into visual categories.

关键词： Object recognition Histograms Image recognition Statistics Wavelet coefficients computer vision Laboratories Numerical analysis computer science Councils

来源：评论

学校读者我要写书评

暂无评论

Classification of carbide distributions using scale selection and directional distributions

Classification of carbide distributions using scale selectio...

引用

IEEE International Conference on Image Processing

作者： K. Wiltschi T. Lindeberg A. Pinz Institute for Computer Graphics and Vision Technical University of Graz Austria Computational Vision and Active Perception Laboratory KTH Stockholm Sweden

We present an automatic method for the classification of steel quality based on scale-space operations. The carbide distribution of microscopic specimen images is assessed by classifying according to so-called 'degree' and 'type' of the specimen. 'Degree' is represented by features extracted with automatic scale selection, and 'type' information is computed from second-moment descriptors. In combination with a morphological verification scheme, this pattern classifier shares large similarities with current manual techniques. Compared to previous work, the new classification scheme has several advantages: the significant scale of the carbide agglomeration is calculated explicitly, and the method is less sensitive to the variance of spatial connectivity than a morphological approach.

关键词： Steel computer vision Microscopy Shape Kernel Detectors computer graphics Laboratories Feature extraction Data mining

来源：评论

学校读者我要写书评

暂无评论

Combination of foveal and peripheral vision for object recognition and pose estimation

Combination of foveal and peripheral vision for object recog...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： M. Bjorkman D. Kragic Centre for Autonomous Systems & Computer Vision and Active Perception Laboratory Royal Institute of Technology Stockholm Sweden

In this paper, we present a real-time vision system that integrates a number of algorithms using monocular and binocular cues to achieve robustness in realistic settings, for tasks such as object recognition, tracking and pose estimation. The system consists of two sets of binocular cameras; a peripheral set for disparity based attention and a foveal one for higher level processes. Thus the conflicting requirements of a wide field of view and high resolution can be overcome. One important property of the system is that the step from task specification through object recognition to pose estimation is completely automatic, combining both appearance and geometric models. Experimental evaluation is performed in a realistic indoor environment with occlusions, clutter, changing lighting and background conditions.

关键词： Object recognition Cameras Machine vision Robustness Layout Image segmentation Image recognition computer vision Real time systems Solid modeling

来源：评论

学校读者我要写书评

暂无评论

Representations for object grasping and learning from experience

Representations for object grasping and learning from experi...

引用

2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Oscar J. Rubio Kai Huebner Danica Kragic Computer Vision and Active Perception Laboratory Centre of Autonomous Systems School of Computer Science and Communication KTH Stockholm Sweden

We study two important problems in the area of robot grasping: i) the methodology and representations for grasp selection on known and unknown objects, and ii) learning from experience for grasping of similar objects. The core part of the paper is the study of different representations necessary for implementing grasping tasks on objects of different complexity. We show how to select a grasp satisfying force-closure, taking into account the parameters of the robot hand and collision-free paths. Our implementation takes also into account efficient computation at different levels of the system regarding representation, description and grasp hypotheses generation.

关键词： Clouds Shape Three dimensional displays Robots Databases Computational modeling Grasping

来源：评论

学校读者我要写书评

暂无评论

Progress in Pattern Recognition, Image Analysis, computer vision, and Applications 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： Eduardo Bayro-Corrochano Jan-Olof Eklundh

ISBN: (数字)9783642102684

ISBN: (纸本)9783642102677

The 14th Iberoamerican Congress on Pattern Recognition (CIARP 2009, C- gresoIberoAmericanodeReconocimientodePatrones)formedthelatestofanow longseriesofsuccessfulmeetingsarrangedbytherapidlygrowingIberoamerican pattern recognition community. The conference was held in Guadalajara, Jalisco, Mexico and organized by the Mexican Association for computer vision, Neural Computing and Robotics (MACVNR). It was sponsodred by MACVNR and ?ve other Iberoamerican PR societies. CIARP 2009 was like the previous conferences in the series supported by the International Association for Pattern Recognition (IAPR). CIARP 2009 attracted participants from all over the world presenting sta- of-the-artresearchon mathematical methods and computing techniques for p- tern recognition, computer vision, image and signal analysis, robot vision, and speech recognition, as well as on a wide range of their applications. This time the conference attracted participants from 23 countries,9 in Ibe- america, and 14 from other parts of the world. The total number of submitted papers was 187, and after a serious review process 108 papers were accepted, all of them with a scienti?c quality above overall mean rating. Sixty-four were selected as oral presentations and 44 as posters. Since 2008 the conference is almost single track, and therefore there was no real grading in quality between oral and poster papers. As an acknowledgment that CIARP has established itself as a high-quality conference, its proceedings appear in the Lecture Notes in computer Science series. Moreover, its visibility is further enhanced by a selection of a set of papers that will be published in a special issue of the journal Pattern Recognition Letters.

关键词： Pattern Recognition Image Processing and computer vision Artificial Intelligence computer Imaging, vision, Pattern Recognition and Graphics Biometrics

来源：评论

学校读者我要写书评

暂无评论

Class-specific material categorisation

Class-specific material categorisation

引用

International Conference on computer vision (ICCV)

作者： B. Caputo E. Hayman P. Mallikarjuna Computational Vision and Active Perception Laboratory School of Computer Science and Communication Royal Institute of Technology Stockholm Sweden

Although a considerable amount of work has been published on material classification, relatively little of it studies situations with considerable variation within each class. Many experiments use the exact same sample, or different patches from the same image, for training and test sets. Thus, such studies are vulnerable to effectively recognising one particular sample of a material as opposed to the material category. In contrast, this paper places firm emphasis on the capability to generalise to previously unseen instances of materials. We adopt an appearance-based strategy, and conduct experiments on a new database which contains several samples of each of eleven material categories, imaged under a variety of pose, illumination and scale conditions. Together, these sources of intra-class variation provide a stern challenge indeed for recognition. Somewhat surprisingly, the difference in performance between various state-of-the-art texture descriptors proves rather small in this task. On the other hand, we clearly demonstrate that very significant gains can be achieved via different SVM-based classification techniques. Selecting appropriate kernel parameters proves crucial. This motivates a novel recognition scheme based on a decision tree. Each node contains an SVM to split one class from all others with a kernel parameter optimal for that particular node. Hence, each decision is made using a different, optimal, class-specific metric. Experiments show the superiority of this approach over several state-of-the-art classifiers

关键词： Conducting materials Image databases Lighting Kernel Robots Pattern recognition Image recognition computer vision Laboratories computer science

来源：评论

学校读者我要写书评

暂无评论

Task modeling in imitation learning using latent variable models

Task modeling in imitation learning using latent variable mo...

引用

IEEE-RAS International Conference on Humanoid Robots

作者： Carl Henrik Ek Dan Song Kai Huebner Danica Kragic Computer Vision & Active Perception Laboratory Center of Autonomous Systems KTH Royal Institute of Technology Stockholm Sweden

An important challenge in robotic research is learning and reasoning about different manipulation tasks from scene observations. In this paper we present a probabilistic model capable of modeling several different types of input sources within the same model. Our model is capable to infer the task using only partial observations. Further, our framework allows the robot, given partial knowledge of the scene, to reason about what information streams to acquire in order to disambiguate the state-space the most. We present results for task classification within and also reason about different features discriminative power for different classes of tasks.

关键词： Data models Robot sensing systems Humans Training Feature extraction Training data

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6页 << < 1 2 3 4 5 6 > >>

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：