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1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition最新文献

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Active part-decomposition, shape and motion estimation of articulated objects: a physics-based approach 主动部分分解，形状和运动估计的铰接对象:一个基于物理的方法
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323938
I. Kakadiaris, Dimitris N. Metaxas, R. Bajcsy
{"title":"Active part-decomposition, shape and motion estimation of articulated objects: a physics-based approach","authors":"I. Kakadiaris, Dimitris N. Metaxas, R. Bajcsy","doi":"10.1109/CVPR.1994.323938","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323938","url":null,"abstract":"We present a novel, robust, integrated approach to segmentation shape and motion estimation of articulated objects. Initially, we assume the object consists of a single part, and we fit a deformable model to the given data using our physics-based framework. As the object attains new postures, we decide based on certain criteria if and when to replace the initial model with two new models. These criteria are based on the model's state and the given data. We then fit the models to the data using a novel algorithm for assigning forces from the data to the two models, which allows partial overlap between them and determination of joint location. This approach is applied iteratively until all the object's moving parts are identified. Furthermore, we define new global deformations and we demonstrate our technique in a series of experiments, where Kalman filtering is employed to account for noise and occlusion.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"37 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131638386","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: 111
Modelled object pose estimation and tracking by a multi-cameras system 基于多相机系统的建模目标姿态估计与跟踪
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323937
Pascal Braud, M. Dhome, J. Lapresté, N. Daucher
{"title":"Modelled object pose estimation and tracking by a multi-cameras system","authors":"Pascal Braud, M. Dhome, J. Lapresté, N. Daucher","doi":"10.1109/CVPR.1994.323937","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323937","url":null,"abstract":"Our paper proposes a new model based approach to locate and track an object in a multi-cameras system: this method does not involve triangulation. If the calibration and the mutual geometry of the acquisition systems are known, it is possible to express the whole set of equations pertaining to each monocular system, in an unique reference system. In this way it is possible to show that based model methods are not restricted to monocular vision and that some techniques generally viewed as purely monocular can be readily extended and integrated to a multi-cameras system. We prove by experiments on sequences of real images that this approach leads to results better than the monocular ones in two directions: better accuracy as many different view points are used; better robustness as the system is able to deal gracefully with the loss of some of the captors.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130981309","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
Salient structure analysis of fluid flow 流体流动凸台结构分析
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323845
Ji Zhong, Thomas S. Huang, R. Adrian
{"title":"Salient structure analysis of fluid flow","authors":"Ji Zhong, Thomas S. Huang, R. Adrian","doi":"10.1109/CVPR.1994.323845","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323845","url":null,"abstract":"This paper presents a framework for analyzing salient patterns (vortex structures) in the velocity fields of turbulent fluid flows. Vortices are modeled as rotational motions in the velocity fields and concentrations in the corresponding vorticity fields. A pointwise linear model is then built to approximate the kinematics of the flow field. Locally, the vector fields are analyzed in terms of fluid motion and singular patterns. The regions of vortex structures are then extracted by identifying those dominated by rotational motion or those of focus-type singularity. In addition to this, 2D vortices, as a special case, are detected by searching regions of vorticity concentrations. The algorithm is applied to both 2D and 3D, experimental and computational turbulent flows.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130526240","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
Reactive view planning for quantification of local geometry 用于局部几何量化的响应式视图规划
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323906
C. Madsen, H. Christensen
{"title":"Reactive view planning for quantification of local geometry","authors":"C. Madsen, H. Christensen","doi":"10.1109/CVPR.1994.323906","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323906","url":null,"abstract":"We present a view point planning strategy for determining the true angle between legs of junctions in a polyhedral scene. The strategy results in a reactive visual behaviour guiding the camera towards a canonical view point producing a fronto-parallel projection of object faces. From these views the angle in the image is identical to the true angle, thus the method does not involve reconstruction. Qualitative visual events, e.g., zero-crossings in the rate-of-change of measured, apparent angle, are used to control the motion of the camera, resulting in independence of positional feedback.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133223825","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
Projective reconstruction from line correspondences
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323922
R. Hartley
{"title":"Projective reconstruction from line correspondences","authors":"R. Hartley","doi":"10.1109/CVPR.1994.323922","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323922","url":null,"abstract":"The paper gives a practical rapid algorithm for doing projective reconstruction of a scene consisting of a set of lines seen in three or more images with uncalibrated cameras. The algorithm is evaluated on real and ideal data to determine its performance in the presence of varying degrees of noise. By carefully consideration of sources of error, it is possible to get accurate reconstruction with realistic levels of noise. The algorithm can be applied to images from different cameras or the same camera. For images with the same camera with unknown calibration, it is possible to do a complete Euclidean reconstruction of the image. This extends to the case of uncalibrated cameras previous results on scene reconstruction from lines,.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125844320","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: 119
Autonomous exploration: driven by uncertainty 自主探索:由不确定性驱动
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323849
P. Whaite, F. Ferrie
{"title":"Autonomous exploration: driven by uncertainty","authors":"P. Whaite, F. Ferrie","doi":"10.1109/CVPR.1994.323849","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323849","url":null,"abstract":"Passively accepting measurements of the world is not enough, as the data we obtain is always incomplete, and the inferences made from it are uncertain to a degree which is often unacceptable. If we are to build machines that operate autonomously they will always be faced with this dilemma, and can only be successful if they play a much more active role. This paper presents such a machine. It deliberately seeks out those parts of the world which maximize the fidelity of its internal representations, and keeps searching until those representations are acceptable. We call this paradigm autonomous exploration, and the machine an a autonomous explorer. This paper has two major contributions. The first is a theory that tells us how to explore, and which confirms the intuitive ideas we have put forward previously. The second is an implementation of that theory. The system is entirely bottom-up and does not depend on a priori knowledge of the environment. To our knowledge it is the first to have successfully closed the loop between gaze planning and the inference of complex 3D models.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125853462","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: 330
Singularity analysis and derivative scale-space 奇异分析与导数尺度空间
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323836
F. Falzon, G. Giraudon
{"title":"Singularity analysis and derivative scale-space","authors":"F. Falzon, G. Giraudon","doi":"10.1109/CVPR.1994.323836","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323836","url":null,"abstract":"The scale-space representations and wavelet transform theory have provided us with good singularity detection frameworks. Thanks to such methods, image understanding processes have become more and more powerful. Some computer vision tasks also require a knowledge on the nature of detected singularities. We propose, in this paper, to take into account these requirements, and we present a singularity detection method based on fractional calculus arguments.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121796432","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
Viewpoint selection for visual search 视觉搜索的视点选择
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323902
L. Wixson
{"title":"Viewpoint selection for visual search","authors":"L. Wixson","doi":"10.1109/CVPR.1994.323902","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323902","url":null,"abstract":"Searching for an object in a cluttered area is often complicated by the fact that the clutter hides portions of the area from view. Multiple viewpoints are often required. Previous viewpoint selection algorithms rely on models that represent the portions already viewed. Unfortunately, these models are often difficult to construct when the sensor position is imprecisely known and when the obtainable depth data is sparse. This paper questions whether scene models are really necessary for selecting viewpoints for search tasks. It investigates two alternative viewpoint selection methods that do not rely on such models. One constructs no representation and simply uses a fitted set of viewpoints, while the other selects viewpoints based on detected occluding edges. On average, both model-free methods compare very favorably to model-based methods, although additional work is necessary to ensure that they abort in a timely manner when the desired object cannot be found.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124870928","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: 40
A study relating image sampling rate and image pattern recognition 图像采样率与图像模式识别的关系研究
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323884
G. Srikantan, S. Srihari
{"title":"A study relating image sampling rate and image pattern recognition","authors":"G. Srikantan, S. Srihari","doi":"10.1109/CVPR.1994.323884","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323884","url":null,"abstract":"The trade-off between the granularity of the data representation and the recognition accuracy is examined in this paper. We show that unless a particular criterion is satisfied, there is no guarantee of achieving a prescribed recognition accuracy. This criterion of interest, is the mutual information content between the measurements and the class identities. A novel method for the objective evaluation of intrinsic error in recognition as sampling rate varies, is described. This approach is general enough to permit the evaluation of error even when the parameter under study takes a different form. To demonstrate this we present results in feature subset selection and multiple classifier combination. In the case of feature selection, the measurements are the features. In the case of multiple classifier combination it is the \"quality\" of the individual classifiers, evalulated based on the mutual information between the classifier parameters and class identities.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"8 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124908194","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
Quantitative performance evaluation of thinning algorithms under noisy conditions 噪声条件下细化算法的定量性能评价
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323779
M. Y. Jaisimha, R. Haralick, D. Dori
{"title":"Quantitative performance evaluation of thinning algorithms under noisy conditions","authors":"M. Y. Jaisimha, R. Haralick, D. Dori","doi":"10.1109/CVPR.1994.323779","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323779","url":null,"abstract":"Thinning algorithms are an important sub-component in the construction of computer vision (especially for optical character recognition (OCR)) systems. Important criteria for the choice of a thinning algorithm include the sensitivity of the algorithms to input shape complexity and to the amount of noise. In previous work, we introduced a methodology to quantitatively analyse the performance of thinning algorithms. The methodology uses an ideal world model for thinning based on the concept of Blum ribbons. In this paper we extend upon this methodology to answer these and other experimental questions of interest. We contaminate the noise-free images using a noise model that simulates the degradation introduced by the process of xerographic copying and laser printing. We then design experiments that study how each of 16 popular thinning algorithms performs relative to the Blum ribbon gold standard and relative to itself as the amount of noise varies. We design statistical data analysis procedures for various performance comparisons. We present the results obtained from these comparisons and a discussion of their implications in this paper.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125577502","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: 15
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