International Conference on Computer Vision Theory and Applications最新文献_第3页

Covariance based Fish Tracking in Real-life Underwater Environment 基于协方差的真实水下环境鱼类跟踪

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-15 DOI: 10.5220/0003866604090414

C. Spampinato, S. Palazzo, D. Giordano, I. Kavasidis, Fang-Pang Lin, Yun-Te Lin

{"title":"Covariance based Fish Tracking in Real-life Underwater Environment","authors":"C. Spampinato, S. Palazzo, D. Giordano, I. Kavasidis, Fang-Pang Lin, Yun-Te Lin","doi":"10.5220/0003866604090414","DOIUrl":"https://doi.org/10.5220/0003866604090414","url":null,"abstract":"In this paper we present a covariance based tracking algorithm for intelligent video analysis to assist marine biologists in understanding the complex marine ecosystem in the Ken-Ding sub-tropical coral reef in Taiwan by processing underwater real-time videos recorded in open ocean. One of the most important aspects of marine biology research is the investigation of fish trajectories to identify events of interest such as fish preying, mating, schooling, etc. This task, of course, requires a reliable tracking algorithm able to deal with 1) the difficulties of following fish that have multiple degrees of freedom and 2) the possible varying conditions of the underwater environment. To accommodate these needs, we have developed a tracking algorithm that exploits covariance representation to describe the object’s appearance and statistical information and also to join different types of features such as location, color intensities, derivatives, etc. The accuracy of the algorithm was evaluated by using hand-labeled ground truth data on 30000 frames belonging to ten different videos, achieving an average performance of about 94%, estimated using multiple ratios that provide indication on how good is a tracking algorithm both globally (e.g. counting objects in a fixed range of time) and locally (e.g. in distinguish occlusions among objects).","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124876375","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: 55

Multi-camera Topology Recovery using Lines 多相机拓扑恢复使用线

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-14 DOI: 10.5220/0002843302450250

Sang Ly, C. Demonceaux, P. Vasseur

引用次数: 0

Fast adaptable skin colour detection in RGB space 快速适应的皮肤颜色检测在RGB空间

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-14 DOI: 10.5220/0002055800030010

M. Tosàs, Steven Mills

引用次数: 0

Signal Activity Estimation with Built-in Noise Management in Raw Digital Images 原始数字图像中内置噪声管理的信号活动估计

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-14 DOI: 10.5220/0004280301180121

A. Bosco, Davide Giacalone, A. Bruna, S. Battiato, Rosetta Rizzo

引用次数: 1

A Faster Method Aiming Iris Extraction 一种快速的虹膜提取方法

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-12 DOI: 10.5220/0004303700900093

J. H. Alves, G. Giraldi, L. A. P. Neves

引用次数: 0

Anisotropic Median Filtering for Stereo Disparity Map Refinement 用于立体视差贴图细化的各向异性中值滤波

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-12 DOI: 10.5220/0004200401890198

Nils Einecke, J. Eggert

引用次数: 22

Prior Knowledge About Camera Motion for Outlier Removal in Feature Matching 基于相机运动先验知识的特征匹配异常点去除

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-12 DOI: 10.5220/0005456406030610

Elisavet (Ellie) Konstantina Stathopoulou, R. Hänsch, O. Hellwich

{"title":"Prior Knowledge About Camera Motion for Outlier Removal in Feature Matching","authors":"Elisavet (Ellie) Konstantina Stathopoulou, R. Hänsch, O. Hellwich","doi":"10.5220/0005456406030610","DOIUrl":"https://doi.org/10.5220/0005456406030610","url":null,"abstract":"The search of corresponding points in between images of the same scene is a well known problem in many computer vision applications. In particular most structure from motion techniques depend heavily on the correct estimation of corresponding image points. Most commonly used approaches make neither assumptions about the 3D scene nor about the relative positions of the cameras and model both as completely unknown. This general model results in a brute force comparison of all keypoints in one image to all points in all other images. In reality this model is often far too general because coarse prior knowledge about the cameras is often available. For example, several imaging systems are equipped with positioning devices which deliver pose information of the camera. Such information can be used to constrain the subsequent point matching not only to reduce the computational load, but also to increase the accuracy of path estimation and 3D reconstruction. This study presents Guided Matching as a new matching algorithm towards this direction. The proposed algorithm outperforms brute force matching in speed as well as number and accuracy of correspondences, given well estimated priors.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116153759","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

An Evaluation Methodology for Stereo Correspondence Algorithms 一种立体对应算法的评价方法

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-11 DOI: 10.5220/0003850801540163

I. Cabezas, M. Trujillo, M. Florian

{"title":"An Evaluation Methodology for Stereo Correspondence Algorithms","authors":"I. Cabezas, M. Trujillo, M. Florian","doi":"10.5220/0003850801540163","DOIUrl":"https://doi.org/10.5220/0003850801540163","url":null,"abstract":"A comparison of stereo correspondence algorithms can be conducted by a quantitative evaluation of disparity maps. Among the existing evaluation methodologies, the Middlebury’s methodology is commonly used. However, the Middlebury’s methodology has shortcomings in the evaluation model and the error measure. These shortcomings may bias the evaluation results, and make a fair judgment about algorithms accuracy difficult. An alternative, the A∗ methodology is based on a multiobjective optimisation model that only provides a subset of algorithms with comparable accuracy. In this paper, a quantitative evaluation of disparity maps is proposed. It performs an exhaustive assessment of the entire set of algorithms. As innovative aspect, evaluation results are shown and analysed as disjoint groups of stereo correspondence algorithms with comparable accuracy. This innovation is obtained by a partitioning and grouping algorithm. On the other hand, the used error measure offers advantages over the error measure used in the Middlebury’s methodology. The experimental validation is based on the Middlebury’s test-bed and algorithms repository. The obtained results show seven groups with different accuracies. Moreover, the topranked stereo correspondence algorithms by the Middlebury’s methodology are not necessarily the most accurate in the proposed methodology.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123503979","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: 6

Vehicle Speed Estimation from Two Images for LIDAR Second Assessment 激光雷达二次评估中两幅图像的车速估计

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-11 DOI: 10.5220/0003855403810386

C. Beumier

{"title":"Vehicle Speed Estimation from Two Images for LIDAR Second Assessment","authors":"C. Beumier","doi":"10.5220/0003855403810386","DOIUrl":"https://doi.org/10.5220/0003855403810386","url":null,"abstract":"Vehicle speed control has been traditionally carried out by RADAR and more recently by LIDAR systems. We present a solution that derives the speed from two images acquired by a static camera and one real dimension from the vehicle. It was designed to serve the purpose of second assessment in case of legal dispute about a LIDAR speed measure. The approach follows a stereo paradigm, considering the equivalent problem of a stationary vehicle captured by a moving camera. 3D coordinates of vehicle points are obtained as the intersection of 3D lines emanating from corresponding points in both images, using the camera pinhole model. The displacement, approximated by a translation, is derived from the best match of reconstructed 3D points, minimising the residual error of 3D line intersection and the deviation with the known dimensions of the licence plate. A graphical interface lets the user select and refine vehicle points, starting with the 4 corners of the licence plate. The plate dimension is selected from a list or typed in. More than 100 speed estimation results confirmed hypothesis about the translation approximation and showed a maximal deviation with LIDAR speed of less than +/10 % as required by the application.","PeriodicalId":411140,"journal":{"name":"International Conference on Computer Vision Theory and Applications","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114206059","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: 2

Driving Warning System Based on Visual Perception of Road Signs 基于路标视觉感知的驾驶预警系统

International Conference on Computer Vision Theory and Applications Pub Date : 2018-08-11 DOI: 10.5220/0001076800540060

J. P. Carrasco, A. D. L. Escalera, J. M. Armingol

引用次数: 0