2014 Canadian Conference on Computer and Robot Vision最新文献

3D Scan Registration Using Curvelet Features 使用曲线特征的3D扫描配准

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.18

Siddhant Ahuja, Steven L. Waslander

引用次数: 6

Towards Estimating Bias in Stereo Visual Odometry 立体视觉里程计中偏差估计的研究

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.10

Sara Farboud-Sheshdeh, T. Barfoot, R. Kwong

{"title":"Towards Estimating Bias in Stereo Visual Odometry","authors":"Sara Farboud-Sheshdeh, T. Barfoot, R. Kwong","doi":"10.1109/CRV.2014.10","DOIUrl":"https://doi.org/10.1109/CRV.2014.10","url":null,"abstract":"Stereo visual odometry (VO) is a common technique for estimating a camera's motion, features are tracked across frames and the pose change is subsequently inferred. This position estimation method can play a particularly important role in environments in which the global positioning system (GPS) is not available (e.g., Mars rovers). Recently, some authors have noticed a bias in VO position estimates that grows with distance travelled, this can cause the resulting position estimate to become highly inaccurate. The goals of this paper are (i) to investigate the nature of this bias in VO, (ii) to propose methods of estimating it, and (iii) to provide a correction that can potentially be used online. We identify two effects at play in stereo VO bias: first, the inherent bias in the maximum-likelihood estimation framework, and second, the disparity threshold used to discard far-away and erroneous stereo observations. In order to estimate the bias, we investigate three methods: Monte Carlo sampling, the sigma-point method (with modification), and an existing analytical method in the literature. Based on simulations, we show that our new sigma point method achieves similar accuracy to Monte Carlo, but at a fraction of the computational cost. Finally, we develop a bias correction algorithm by adapting the idea of the bootstrap in statistics, and demonstrate that our bias correction algorithm is capable of reducing approximately 95% of bias in VO problems without incorporating other sensors into the setup.","PeriodicalId":385422,"journal":{"name":"2014 Canadian Conference on Computer and Robot Vision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131517702","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: 7

A Proof-of-Concept Demonstration of Visual Teach and Repeat on a Quadrocopter Using an Altitude Sensor and a Monocular Camera 使用高度传感器和单目摄像机在四旋翼飞行器上进行视觉教学和重复的概念验证演示

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.40

Andreas Pfrunder, Angela P. Schoellig, T. Barfoot

引用次数: 29

Multiple Feature Fusion in the Dempster-Shafer Framework for Multi-object Tracking Dempster-Shafer框架中多目标跟踪的多特征融合

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.49

Dorra Riahi, Guillaume-Alexandre Bilodeau

引用次数: 10

Grid Seams: A Fast Superpixel Algorithm for Real-Time Applications 网格接缝:用于实时应用的快速超像素算法

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.25

P. Siva, A. Wong

引用次数: 12

Projected Barzilai-Borwein Method with Infeasible Iterates for Nonnegative Least-Squares Image Deblurring 非负最小二乘图像去模糊的不可行迭代投影Barzilai-Borwein方法

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.33

Kathleen Fraser, D. Arnold, G. Dellaire

引用次数: 1

Outdoor Ice Accretion Estimation of Wind Turbine Blades Using Computer Vision 基于计算机视觉的风力发电机叶片室外冰积估算

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.41

M. Akhloufi, Nassim Benmesbah

引用次数: 13

Drums: A Middleware-Aware Distributed Robot Monitoring System 鼓:中间件感知分布式机器人监控系统

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1145/2843966.2843974

Valiallah Monajjemi, Jens Wawerla, R. Vaughan

引用次数: 12

Identification of Morphologically Similar Seeds Using Multi-kernel Learning 利用多核学习识别形态相似种子

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.27

Xin Yi, M. Eramian, Ruojing Wang, E. Neufeld

{"title":"Identification of Morphologically Similar Seeds Using Multi-kernel Learning","authors":"Xin Yi, M. Eramian, Ruojing Wang, E. Neufeld","doi":"10.1109/CRV.2014.27","DOIUrl":"https://doi.org/10.1109/CRV.2014.27","url":null,"abstract":"Use of digital image analysis for the identification of seeds has not been recognized as a validated method. Image analysis for seed identification has been previously studied, and good recognition rates have been achieved. However, the data sets used in these experiments either contain very few groups of non-verified specimens or little representation of intra-species variations. This study considered a data set containing seed specimens that were verified to represent the species and a typical population variation, as well as look-alike species that share the same morphological appearance, in particular, seeds from species in the same genus, which can be particularly difficult for even trained professionals to visually distinguish. With representative specimens, the image features and machine learning algorithms described herein can achieve a high recognition rate: >97%. Three different types of features from seed images: colour, shape, and texture were extracted, and a multi-kernel support vector machine was used as the classifier. We compared our features to the previous state-of-the-art features and the results showed that the features we selected performed better on our data set.","PeriodicalId":385422,"journal":{"name":"2014 Canadian Conference on Computer and Robot Vision","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122669776","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: 3

Construction of a Mean Surface for the Variability Study of the Cornea 角膜变异性研究中平均曲面的构造

2014 Canadian Conference on Computer and Robot Vision Pub Date : 2014-05-06 DOI: 10.1109/CRV.2014.51

A. Polette, E. Auvinet, J. Mari, I. Brunette, J. Meunier

引用次数: 5