检索结果-内蒙古大学图书馆

Communications in computer and Information Science 2013年 384卷 70-79页

作者： Moutafi, Konstantina Vergeti, Paraskevi Alexakos, Christos Dimitrakopoulos, Christos Giotopoulos, Konstantinos Antonopoulou, Hera Likothanassis, Spiros Pattern Recognition Lab. Dept. of Computer Engineering and Informatics University of Patras Greece Technological Educational Institute of Patras Greece

The specific contribution aims to provide a web-based adaptive Learning Management System (LMS), named EVMATHEIA, which integrates specific innovative fundamental aspects of Student Learning Style and Intelligent Self-Assessment Mechanisms. More specifically the proposed adaptive system encapsulates an integrated student model that facilitates the decision about the learning style of the student monitoring his/her behavior. Furthermore, the platform utilizes semantic modeling techniques for the representation of the knowledge, semantically annotated educational material and an intelligent mechanism for the self-assessment and recommendation process. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Real-time range imaging in health care: A survey

Real-time range imaging in health care: A survey

引用

Dagstuhl 2012 Seminar on Time-of-Flight Imaging: Sensors, Algorithms, and Applications and Workshop on Imaging New Modalities, Held at the German Conference on pattern recognition, GCPR2013

作者： Bauer, Sebastian Seitel, Alexander Hofmann, Hannes Blum, Tobias Wasza, Jakob Balda, Michael Meinzer, Hans-Peter Navab, Nassir Hornegger, Joachim Maier-Hein, Lena Pattern Recognition Lab. Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Germany Junior Group: Computer-assisted Interventions Germany Heidelberg Germany Metrilus GmbH Erlangen Germany Technische Universität München Munich Germany

ISBN: (纸本)9783642449635

The recent availab.lity of dynamic, dense, and low-cost range imaging has gained widespread interest in health care. It opens up new opportunities and has an increasing impact on both research and commercial activities. This chapter presents a state-of-the-art survey on the integration of modern range imaging sensors into medical applications. The scope is to identify promising applications and methods, and to provide an overview of recent developments in this rapidly evolving domain. The survey covers a broad range of topics, including guidance in computer-assisted interventions, operation room monitoring and workflow analysis, touch-less interaction and on-patient visualization, as well as prevention and support in elderly care and rehabilitation. We put emphasis on dynamic and interactive tasks where real-time and dense 3-D imaging forms the key aspect. While considering different range imaging modalities that fulfill these requirements, we particularly investigate the impact of Time-of-Flight imaging in this domain. Eventually, we discuss practical demands and limitations, and open research issues and challenges that are of fundamental importance for the progression of the field. © Springer-Verlag 2013.

关键词： Surveys

来源：评论

学校读者我要写书评

暂无评论

Complex 3D General Object Reconstruction from Line Drawings

Complex 3D General Object Reconstruction from Line Drawings

引用

International Conference on computer vision (ICCV)

作者： Linjie Yang Jianzhuang Liu Xiaoou Tang Department of Information Engineering Chinese University of Hong Kong Shenzhen Key Lab of Computer Vision and Pattern Recognition Chinese Academy of Sciences China

ISBN: (纸本)9781479928415

An important topic in computer vision is 3D object reconstruction from line drawings. Previous algorithms either deal with simple general objects or are limited to only manifolds (a subset of solids). In this paper, we propose a novel approach to 3D reconstruction of complex general objects, including manifolds, non-manifold solids, and nonsolids. Through developing some 3D object properties, we use the degree of freedom of objects to decompose a complex line drawing into multiple simpler line drawings that represent meaningful building blocks of a complex object. After 3D objects are reconstructed from the decomposed line drawings, they are merged to form a complex object from their touching faces, edges, and vertices. Our experiments show a number of reconstruction examples from both complex line drawings and images with line drawings superimposed. Comparisons are also given to indicate that our algorithm can deal with much more complex line drawings of general objects than previous algorithms.

关键词： Solids Three-dimensional displays Manifolds Image reconstruction computer vision Search problems Image edge detection

来源：评论

学校读者我要写书评

暂无评论

A semantic model for video based face recognition

A semantic model for video based face recognition

引用

International Conference on Information and Automation (ICIA)

作者： Dihong Gong Kai Zhu Zhifeng Li Yu Qiao Shenzhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781479913329

Video-based face recognition has attracted a great deal of attention in recent years due to its wide applications. The challenge of video-based face recognition comes from several aspects. First, video data involves many frames, which increases data size and processing complexity. Second, key frames extracted from videos are usually of high intra-personal discrepancy due to variations in expressions, poses, and illuminations. In order to address these problems, we propose a novel semantic based subspace model to improve the performance of video based face recognition. The basic idea is to construct an appropriate low-dimensional subspace for each person, upon which a semantic model is built to classify the key frames of the person into specific class. After the semantic classification, the key frames belonging to the same classes, i.e. the same semantics, are used to train the linear classifiers for recognition. Extensive experiments on a large face video database (XM2VTS) clearly show that our approach obtains a significant performance improvement over the traditional approaches.

关键词： Face Training Face recognition Semantics Video sequences Principal component analysis Probes

来源：评论

学校读者我要写书评

暂无评论

LTD: Local Ternary Descriptor for Image Matching

LTD: Local Ternary Descriptor for Image Matching

引用

IEEE International Conference on Information and Automation

作者： Yongqiang Gao Yu Qiao Zhifeng Li Chunjing Xu Shenzhen Key Lab. of Comput. Vision &amp Pattern Recognition Shenzhen Inst. of Adv. Technol. Chinese Univ. of Hong Kong Shenzhen China|c|

ISBN: (纸本)9781479913329

Binary descriptors are receiving extensive research interests due to their storage and computation efficiency. A good binary descriptor should deliver sufficient information as well as be robust to image deformation and distortion. Recently, Calonder et al proposed Binary Robust Independent Elementary Features (BRIEF), which showed good performance in image matching. In this paper, we extend BRIEF to a Local Ternary Descriptor (LTD). Compared with BRIEF, LTD introduces a threshold to describe the difference of two pixels into three values. Our ternary descriptor can deliver more discriminative information than BRIEF while being robust to image deformation. We examine the key-point matching performance of LTD on several public datasets. The experimental results exhibit that LTD outperforms BRIEF.

关键词： local ternary descriptor descriptors binary pattern Hamming distance

来源：评论

学校读者我要写书评

暂无评论

Compressed sensing ensemble classifier for human detection

Compressed sensing ensemble classifier for human detection

引用

4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013

作者： Zhang, Baochang Liu, Juan Gao, Yongsheng Liu, Jianzhuang Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering BeiHang University Beijing 100191 China School of Engineering Griffith University Australia Shenzhen Key Lab for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Information Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9783642420566

This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of base classifiers. The major contributions of this paper are: 1) a novel principled framework for ensemble classifier design based on compressed sensing;2) a new concept of considering both the simplicity of ensemble classifier and irrelevance of base classifiers towards optimal classifier design;and 3) a quadratic function for CSEC optimization which includes a new optimizable positive semi-definite relevance matrix to simultaneously select appropriate base classifiers with minimized relevance. Experimental results on INRIA and SDL databases show that the performance of CSEC is better than two most popular classifiers SVM and AdaBoost, as well as a most recent method CLML. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

Signature segmentation and recognition from scanned documents

Signature segmentation and recognition from scanned document...

引用

International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Ranju Mandal Partha Pratim Roy Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Queensland Australia Automation Engineering Department Synchromedia Lab Montreal Canada Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Signature as a query is important for content-based document image retrieval from a scanned document repository. This paper presents a two-stage approach towards automatic signature segmentation and recognition from scanned document images. In the first stage, signature blocks are segmented from the document using word-wise component extraction and classification. Gradient based features are extracted from each component at the word level to perform the classification task. In the 2nd stage, SIFT (Scale-Invariant Feature Transform) descriptors and Spatial Pyramid Matching (SPM)-based approaches are used for signature recognition. Support Vector Machines (SVMs) are employed as the classifier for both levels in this experiment. The experiments are performed on the publicly availab.e “Tobacco-800” and GPDS [1] datasets and the results obtained from the experiments are promising.

关键词： Image segmentation Industries Vector quantization Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

ONLINE ADAPTIVE DICTIONARY LEARNING AND WEIGHTED SPARSE CODING FOR ABNORMALITY DETECTION

ONLINE ADAPTIVE DICTIONARY LEARNING AND WEIGHTED SPARSE CODI...

引用

IEEE International Conference on Image Processing

作者： Sheng Han Ruiqing Fu Suzhen Wang Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong

ISBN: (纸本)9781479923427

This paper focuses mainly on adaptive dictionary updating and abnormality detection via weighted space coding in video surveillance. Generally, abnormality analysis conducted on a large amount of video data is very complicated, time-consuming and time-variant. However, our dictionary is very efficient at following up on shifted contents in video and abandoning old inactive information in time. The adaptability characteristic also helps reduce the dictionary's size to a small scale, since it only needs to keep recent or active information. We also introduce a simple, but effective, judgement criterion for abnormal detection based on sparse coding over weighted bases. Because of the condensed dictionary and the simplified judgment criterion, our algorithm performs online learning and online detection with a high speed and a high accuracy in various scenes.

关键词： Dictionary Learning Adaptive Learning Sparse Coding Abnormality Detection Sparse coding anomaly detection video data Dictionaries as Topic video monitoring

来源：评论

学校读者我要写书评

暂无评论

Medical image segmentation employing information gain and fuzzy c-means algorithm

Medical image segmentation employing information gain and fu...

引用

International Conference on Open Source Systems and Technologies (ICOSST)

作者： Mehdi Hassan Asmatullah Chaudhry Asifullah Khan M. Aksam Iftikhar Jin Young Kim Pattern Recognition Lab. Islamabad Pakistan NDTG Islamabad Pakistan Pakistan Institute of Engineering and Applied Sciences Islamabad PK Department of Electronics and Computer Engineering Chonnam National University Gwangju S. Korea

In this paper, we proposed a new approach for image clustering to address the adverse effects of noise presented in the images. In particular, the concept of information gain has been incorporated into classical fuzzy c-means (FCM) algorithm in order to develop a robust clustering method. FCM is associated with high sensitivity to noise and produces non-homogenous clustering. To induce robustness to noise, the new clustering technique updates fuzzy membership values and cluster centroids based on information gain. The proposed method produces more homogeneous clustering and its performance can be verified at noisy and noise free images. Experiments have been performed on synthetic, CT liver images and compared with those of classical FCM and one of its robust variants. Moreover, the proposed algorithm has been validated on a data set of 30 carotid artery ultrasound images. Visual inspection of segmented images and clustering quality measures confirm that the proposed approach outperforms other clustering algorithms in comparison. Quantitative measures, in terms of PC and CE, also lead to similar conclusion. Hence, the proposed algorithm is robust to noise and produces homogenous clustering.

关键词： Image segmentation Clustering algorithms Biomedical imaging Liver Computed tomography Carotid arteries Noise

来源：评论

学校读者我要写书评

暂无评论

Classification of gothic and baroque architectural elements

Classification of gothic and baroque architectural elements

引用

2012 19th International Conference on Systems, Signals and Image Processing, IWSSIP 2012

作者： Shalunts, Gayane Haxhimusa, Yll Sablatnig, Robert Institute of Computer Aided Automation Computer Vision Lab. Vienna University of Technology Austria Institute of Computer Graphics and Algorithms Pattern Recognition and Image Processing Lab. Vienna University of Technology Austria

ISBN: (纸本)9783200023284

Architectural elements are the components and details of buildings. Their unique set, combination, design, construction technique form the architectural style of buildings. Building facade classification by architectural styles is viewed as a task of classifying separate architectural structural elements. In the scope of building facade architectural style classification the current paper targets the problem of classification of Gothic and Baroque architectural elements called tracery, pediment and balustrade. Since certain gradient directions dominate on the shape of each architectural element, discrimination between dominating gradients means classification of architectural elements and thus architectural styles. We use local features to describe gradient directions. Our approach is based on clustering and learning of local features and yields a high classification rate. © 2012 Institute of Telecommunica.

关键词： Classification (of information)

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：