2010 Canadian Conference on Computer and Robot Vision最新文献_第3页

The Sentinel Problem for a Multi-hop Sensor Network 多跳传感器网络的哨兵问题

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.40

D. Marinakis, S. Whitesides

引用次数: 2

Texture CLassification Using Compressed Sensing 使用压缩感知的纹理分类

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.16

Li Liu, P. Fieguth

{"title":"Texture CLassification Using Compressed Sensing","authors":"Li Liu, P. Fieguth","doi":"10.1109/CRV.2010.16","DOIUrl":"https://doi.org/10.1109/CRV.2010.16","url":null,"abstract":"This paper presents a simple, novel, yet very powerful approach for texture classification based on compressed sensing and bag of words model, suitable for large texture database applications with images obtained under unknown viewpoint and illumination. At the feature extraction stage, a small set of random features are extracted from local image patches. The random features are embedded into the bag of words model to perform texture classification. Random feature extraction surpasses many conventional feature extraction methods, despite their careful design and complexity. We conduct extensive experiments on the CUReT database to evaluate the performance of the proposed approach. It is demonstrated that excellent performance can be achieved by the proposed approach using a small number of random features, as long as the dimension of the feature space is above certain threshold. Our approach is compared with recent state-of-the-art methods: the Patch method (Varma and Zisserman, TPAMI 09), the MR8 filter bank method (Varma and Zisserman, IJCV 05) and the LBP method (Ojala et al., TPAMI 02). It is shown that the proposed method significantly outperforms MR8 and LBP and is at least as good as the Patch method with drastic reduction in storage and computational complexity.","PeriodicalId":358821,"journal":{"name":"2010 Canadian Conference on Computer and Robot Vision","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134258034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Efficient Augmentation of the EKF Structure from Motion with Frame-to-Frame Features 基于帧间特征的运动EKF结构有效增强

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.13

Adel H. Fakih, J. Zelek

{"title":"Efficient Augmentation of the EKF Structure from Motion with Frame-to-Frame Features","authors":"Adel H. Fakih, J. Zelek","doi":"10.1109/CRV.2010.13","DOIUrl":"https://doi.org/10.1109/CRV.2010.13","url":null,"abstract":"The Extended Kalman Filter (EKF) is still one of the most widely used approaches for small scale Structure from Motion (SFM) and Simultaneous Localization And Mapping (SLAM) problems. However, the EKF does not have the ability to take into account the motion information carried by features matched only between two consecutive frames. This information is valuable because, when used appropriately, it generally enhances the performance of the filter. Two main reasons hinder the direct use of such features in the EKF: their un-initialized 3D location would corrupt the covariance matrix, and the computational cost grows cubically with the number of features. In this paper we present a novel approach to solve those problems. Our approach folds the frame-to-frame information in the filter through a separate update step that can be carried out in linear time. Other advantages of our approach is that it can be introduced to already implemented filters with minimal change. It can be done in a separate thread to further speedup the computation. Additionally, it can be further divided to multiple steps with different sets of features, which permits to reject or accept each step based on some performance criteria and to stay within the budgeted time.","PeriodicalId":358821,"journal":{"name":"2010 Canadian Conference on Computer and Robot Vision","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133016055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multispectral Face Recognition in Texture Space 纹理空间中的多光谱人脸识别

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.20

A. Bendada, M. Akhloufi

引用次数: 23

Object Inter-camera Tracking with Non-overlapping Views: A New Dynamic Approach 基于非重叠视图的摄像机间目标跟踪:一种新的动态方法

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.53

Trevor Montcalm, B. Boufama

{"title":"Object Inter-camera Tracking with Non-overlapping Views: A New Dynamic Approach","authors":"Trevor Montcalm, B. Boufama","doi":"10.1109/CRV.2010.53","DOIUrl":"https://doi.org/10.1109/CRV.2010.53","url":null,"abstract":"Disjoint inter-camera object tracking is the task of tracking objects across video-surveillance cameras that have non-overlapping views. Unlike the closely related task of single-camera tracking, disjoint inter-camera tracking is difficult due to the gaps in observation as an object moves between camera views. To overcome this problem, appearance profiles of the objects seen in each camera are built and used for matching/tracking across different cameras. This paper proposes a new method that uses multiple features that are dynamically weighed for matching moving objects (people in our case) across cameras. In particular, the Zernike moment shape descriptor has been used together with blob histogram and other features to describe a moving object. Weighting emphasis is given to the better features, based on their stability, reliability and their time in the system (how recent they are). This weighting is used both during appearance aggregation and object comparison. Our experiments with real videos have shown the success of our proposed method even in difficult situations where the cameras used are different in terms of brand, quality and resolution.","PeriodicalId":358821,"journal":{"name":"2010 Canadian Conference on Computer and Robot Vision","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114933393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Automated Classification of Operational SAR Sea Ice Images 操作SAR海冰图像的自动分类

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.59

S. Ochilov, David A Clausi

引用次数: 12

Curious George: An Integrated Visual Search Platform 好奇的乔治:一个集成的视觉搜索平台

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.21

D. Meger, Marius Muja, S. Helmer, Ankur Gupta, Catherine Gamroth, Tomas Hoffman, Matthew A. Baumann, T. Southey, Pooyan Fazli, W. Wohlkinger, P. Viswanathan, J. Little, D. Lowe, J. Orwell

{"title":"Curious George: An Integrated Visual Search Platform","authors":"D. Meger, Marius Muja, S. Helmer, Ankur Gupta, Catherine Gamroth, Tomas Hoffman, Matthew A. Baumann, T. Southey, Pooyan Fazli, W. Wohlkinger, P. Viswanathan, J. Little, D. Lowe, J. Orwell","doi":"10.1109/CRV.2010.21","DOIUrl":"https://doi.org/10.1109/CRV.2010.21","url":null,"abstract":"This paper describes an integrated robot system, known as Curious George, that has demonstrated state-of-the-art capabilities to recognize objects in the real world. We describe the capabilities of this system, including: the ability to access web-based training data automatically and in near real-time, the ability to model the visual appearance and 3D shape of a wide variety of object categories, navigation abilities such as exploration, mapping and path following, the ability to decompose the environment based on 3D structure, allowing for attention to be focused on regions of interest, the ability to capture high-quality images of objects in the environment, and finally, the ability to correctly label those objects with high accuracy. The competence of the combined system has been validated by entry into an international competition where Curious George has been among the top performing systems each year. We discuss the implications of such successful object recognition for society, and provide several avenues for potential improvement.","PeriodicalId":358821,"journal":{"name":"2010 Canadian Conference on Computer and Robot Vision","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129050487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

A Bayesian Information Flow Approach to Image Segmentation 基于贝叶斯信息流的图像分割方法

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.46

A. Mishra, A. Wong, David A Clausi, P. Fieguth

引用次数: 1

Multi-Layer Atlas System for Map Management 面向地图管理的多层地图集系统

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.34

Jean-Luc Bedwani, Ioannis M. Rekleitis, F. Michaud, E. Dupuis

引用次数: 3

Bayesian Identity Clustering 贝叶斯同一性聚类

2010 Canadian Conference on Computer and Robot Vision Pub Date : 2010-05-31 DOI: 10.1109/CRV.2010.12

S. Prince, J. Elder

引用次数: 13