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The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)最新文献

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Spatial decomposition of the Hough transform 霍夫变换的空间分解
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.76
James Allan Heather, X. Yang
{"title":"Spatial decomposition of the Hough transform","authors":"James Allan Heather, X. Yang","doi":"10.1109/CRV.2005.76","DOIUrl":"https://doi.org/10.1109/CRV.2005.76","url":null,"abstract":"In the field of image processing, it is a common problem to search for edges within an image, typically using the Hough transform, and attempt to extract the end points of those edges. This paper discusses an improved technique for accomplishing this task. The idea is based on the observation of an additive property of the Hough transform. That is, the global Hough Transform can be obtained by the summation of local Hough transforms of disjoint sub-regions. The method discussed involves the recursive subdivision of the image into sub-images, each with their own parameter space, and organized in a quadtree structure, which allows for implicit storage of arbitrary parameter space manifolds. This method results in improved efficiency in finding endpoints of line segments and improved robustness and reliability in extracting lines in noisy situations, at a slightly increased cost of memory. The new algorithm is presented in detail, along with a discussion of time and space complexities. The paper is concluded with proposed future research in this direction.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121843453","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: 9
An automatic segmentation combining mixture analysis and adaptive region information: a level set approach 结合混合分析和自适应区域信息的自动分割:一种水平集方法
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.14
M. S. Allili, D. Ziou
{"title":"An automatic segmentation combining mixture analysis and adaptive region information: a level set approach","authors":"M. S. Allili, D. Ziou","doi":"10.1109/CRV.2005.14","DOIUrl":"https://doi.org/10.1109/CRV.2005.14","url":null,"abstract":"In this paper, we propose a novel automatic framework for variational color image segmentation based on unifying adaptive region information and mixture modelling. We consider a formulation of the region information by using the posterior probability of a mixture of general Gaussian (GG) pdfs, where each region is represented by a pdf. The segmentation is formulated by the minimization of an energy functional according to the region contours and all the mixture parameters respectively. Two main objectives are achieved by the approach. A scheme is provided to extend easily the adaptive segmentation to an arbitrary number of regions and to perform it in a fully automatic fashion. Moreover, the segmentation recovers an accurate and representative mixture of pdfs. In the approach, we couple the boundary and region information of the image to steer the segmentation. We validate the method on the segmentation of real world color images.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"232 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121301275","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: 9
People tracking using robust motion detection and estimation 人跟踪采用鲁棒运动检测和估计
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.60
Markus Latzel, Emilie Darcourt, John K. Tsotsos
{"title":"People tracking using robust motion detection and estimation","authors":"Markus Latzel, Emilie Darcourt, John K. Tsotsos","doi":"10.1109/CRV.2005.60","DOIUrl":"https://doi.org/10.1109/CRV.2005.60","url":null,"abstract":"Real world computer vision systems highly depend on reliable, robust retrieval of motion cues to make accurate decisions about their surroundings. In this paper, we present a simple, yet high performance low-level filter for motion tracking in digitized video signals. The algorithm is based on constant characteristics of a common, 2-frame interlaced video signal, yet results presented in this paper show its applicability to highly compressed, noisy image sequences as well. In general, our approach uses a computationally low-cost solution to define the area of interest for tracking of multiple, moving objects. Despite its simplicity, it compares very well to existing approaches due to its robustness towards environmental changes. To demonstrate this, we present results of processing a sequence of JPEG-compressed monocular images of a parking lot in order to track pedestrians, cars and bicycles. Despite a high level of noise and changing lighting conditions, the algorithm successfully segments a moving object and tracks its position along a trajectory.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116527901","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: 5
Head tracking with shape modeling and detection 头部跟踪与形状建模和检测
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.46
Maolin Chen, S. Kee
{"title":"Head tracking with shape modeling and detection","authors":"Maolin Chen, S. Kee","doi":"10.1109/CRV.2005.46","DOIUrl":"https://doi.org/10.1109/CRV.2005.46","url":null,"abstract":"Color-based tracking has proved efficient and robust recently. Trackers build the object appearance model with histogram statistics, search and evaluate hypothesis in a probabilistic framework. This method relies much on the discrimination between object and scene blobs. Color clutter in the scene, although not so many in quantity, may distract these trackers. We build explicitly object shape model and insert the head detector into the observation model to resist these clutters in the scene for improved tracker. The detector scans the image and output probability value as the possibility of current window being a candidate human head. Experiments demonstrate the method can work more accurately and robustly.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114711979","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
Segmentation and feature extraction to evaluate the stomach dynamic 分割和特征提取来评价胃的动态
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.73
M. Benjelloun
{"title":"Segmentation and feature extraction to evaluate the stomach dynamic","authors":"M. Benjelloun","doi":"10.1109/CRV.2005.73","DOIUrl":"https://doi.org/10.1109/CRV.2005.73","url":null,"abstract":"Our work is motivated by a practical application of motion study induced by breathing in the abdomen under the influence of diaphragm pressure. In this article, we present an image processing method to analyze the motion of the stomach between expiration and inspiration. Our approach is based on a preliminary edge detection. To extract useful information, we propose two techniques lying respectively on filling and active contour algorithms. The results of both methods are analysed and compared to those obtained manually. In order to improve the results and to overcome the limitations of the proposed edge detector, an edge closing method based on a polynomial contour fitting is applied.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"102 s1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120835441","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: 1
Face detection using combinations of classifiers 使用分类器组合的人脸检测
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.40
Geovany A. Ramírez, O. Fuentes
{"title":"Face detection using combinations of classifiers","authors":"Geovany A. Ramírez, O. Fuentes","doi":"10.1109/CRV.2005.40","DOIUrl":"https://doi.org/10.1109/CRV.2005.40","url":null,"abstract":"In this paper we present a two-stage face detection system. The first stage reduces the search space using two heuristics in cascade: 1) in a face image, the average intensity of the eyes is lower than the intensity of the part between the eyes, and 2) the histograms of the grayscale image of a face with uniform lighting have a distinguishable shape. In the second stage we use combinations of different classifiers including: naive Bayes (NB), support vector machine (SVM), voted perceptron (VP), C4.5 rule induction and feedforward artificial neural network (ANN); we also propose a simple lighting correction method. We use the BioID face dataset to test our system achieving up to a 95.13% of correct detections.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127557345","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: 14
A new photo consistency test for voxel coloring 体素着色的新照片一致性测试
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.9
Jianfeng Yin, J. Cooperstock
{"title":"A new photo consistency test for voxel coloring","authors":"Jianfeng Yin, J. Cooperstock","doi":"10.1109/CRV.2005.9","DOIUrl":"https://doi.org/10.1109/CRV.2005.9","url":null,"abstract":"Volumetric scene reconstruction is an important task for many vision applications. Most voxel coloring or space carving techniques required for this purpose suffer from the coupled problems of visibility and photo consistency. We propose a new photo consistency measurement that implicitly solves the visibility problem, thus permitting an efficient, single-scan voxel inspection that can be parallelized.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123804206","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
A unified stochastic model for detecting and tracking faces 人脸检测与跟踪的统一随机模型
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.12
Sachin Gangaputra, D. Geman
{"title":"A unified stochastic model for detecting and tracking faces","authors":"Sachin Gangaputra, D. Geman","doi":"10.1109/CRV.2005.12","DOIUrl":"https://doi.org/10.1109/CRV.2005.12","url":null,"abstract":"We propose merging face detection and face tracking into a single probabilistic framework. The motivation stems from a broader project in algorithmic modeling, centered on the design and analysis of the online computational process in visual recognition. Detection is represented as a tree-structured graphical network in which likelihoods are assigned to each history or \"trace\" of processing, thereby introducing a new probabilistic component into coarse-to-fine search strategies. When embedded within a temporal Markov framework, the resulting tracking system yields encouraging results.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115329563","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
Resampling 4D images using adaptive filtering 使用自适应滤波对4D图像进行重采样
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.69
Alexander Andreopoulos, John K. Tsotsos
{"title":"Resampling 4D images using adaptive filtering","authors":"Alexander Andreopoulos, John K. Tsotsos","doi":"10.1109/CRV.2005.69","DOIUrl":"https://doi.org/10.1109/CRV.2005.69","url":null,"abstract":"We present an adaptive filtering based methodology for resampling 3D time series images using an extension of the method presented by simultaneously reducing the artifacts due to image noise and resample the data on a finer grid along the time dimension. This provides a methodology for obtaining high quality image resampling without the disadvantages of staircase artifacts created by more common interpolation methods such as linear interpolation. We present qualitative results of the algorithm on a data set of 4D cardiac MRI. This is a useful approach for any situation where we have a data set of 4D images needing to be resampled.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127440044","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
Structure from motion using SIFT features and the PH transform with panoramic imagery 利用SIFT特征和全景图像的PH变换从运动中提取结构
The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) Pub Date : 2005-05-09 DOI: 10.1109/CRV.2005.78
M. Fiala
{"title":"Structure from motion using SIFT features and the PH transform with panoramic imagery","authors":"M. Fiala","doi":"10.1109/CRV.2005.78","DOIUrl":"https://doi.org/10.1109/CRV.2005.78","url":null,"abstract":"Omni-directional sensors are useful in obtaining a 360/spl deg/ field of view of a scene for robot navigation, scene modeling, and telepresence. A method is presented to recover 3D scene structure and camera motion from a sequence of multiple images captured by an omnidirectional catadioptric camera. This 3D model is then used to localize other panoramic images taken in the vicinity. This goal is achieved by tracking the trajectories of SIFT keypoints, and finding the path they travel by utilizing a Hough transform technique modified for panoramic imagery. This technique is applied to spatio-temporal feature extraction in the three-dimensional space of an image sequence, as that scene points trace a horizontal line trajectory relative to the camera. SIFT (scale invariant feature transform) keypoints are distinctive image features which can be identified between images invariant to scale and rotation. Together these methods are applied to reconstruct a three-dimensional model from a sequence of panoramic images, where the panoramic camera was translating in a straight line horizontal path. Only the camera/mirror geometry is known a priori. The camera positions and the world model is determined, up to a scale factor. Experimental results of model building and camera localization using this model are shown.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133281459","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: 11
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