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

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Initializing snakes [object delineation] 初始化蛇[对象描述]
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323783
W. Neuenschwander, P. Fua, G. Székely, O. Kübler
{"title":"Initializing snakes [object delineation]","authors":"W. Neuenschwander, P. Fua, G. Székely, O. Kübler","doi":"10.1109/CVPR.1994.323783","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323783","url":null,"abstract":"We propose a snake-based approach that lets a user specify only the distant end points of the curve he wishes to delineate without having to supply an almost complete polygonal approximation. We achieve much better convergence properties than those of traditional snakes by using the image information around these end points to provide boundary conditions and by introducing an optimization schedule that allows the snake to take image information into account first only near its extremities and then, progressively, towards its center. These snakes could be used to alleviate the often repetitive task practitioners have to face when segmenting images by abolishing the need to sketch a feature of interest in its entirety, that is, to perform a painstaking, almost complete, manual segmentation.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"73 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":"127615761","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: 36
Automatic selection of tuning parameters for feature extraction sequences 自动选择调谐参数的特征提取序列
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323780
V. Ramesh, R. Haralick, Xining Zhang, Desikachari Nadadur, Kenneth B. Thornton
{"title":"Automatic selection of tuning parameters for feature extraction sequences","authors":"V. Ramesh, R. Haralick, Xining Zhang, Desikachari Nadadur, Kenneth B. Thornton","doi":"10.1109/CVPR.1994.323780","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323780","url":null,"abstract":"Computer vision algorithms are composed of different sub-algorithms often applied in sequence. Previous work on performance characterization illustrated how random perturbation models can be setup at various stages of an algorithm sequence for the input and output data. In this paper we address the issue of how one could utilize these random perturbation models in order to automate the selection of free parameters used in an algorithm sequence. We consider an operation sequence that involves edge finding, linking, corner finding and matching. Appropriate prior distributions for the parameters that describe the graytone/geometric characteristics of the image features are specified and validated by using an annotation process. The annotation process involves the manual specification (outlining) of the geometry and spatial extent of the image features. Statistics are gathered for parameters describing features of interest and non-interest (clutter features). The appropriate prior distributions are used to derive the theoretical expressions for feature detector performance over a given image population. These performance measures are then optimized to determine the tuning parameters for the feature detector(s).<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"71 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":"123747094","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: 16
Model-based next view planning by using rules-automatic feature prediction and detection 基于模型的下一个视图规划，采用规则自动特征预测和检测
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323896
Huiqun Liu, X. Lin
{"title":"Model-based next view planning by using rules-automatic feature prediction and detection","authors":"Huiqun Liu, X. Lin","doi":"10.1109/CVPR.1994.323896","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323896","url":null,"abstract":"This paper proposes an effective next view planning strategy for the object recognition and localization task in a model-based robot vision system. A set of rules are designed to automatically predict new features and calculate the next optimal placement of the sensor so that the most useful information can be gathered from multi-views. A state vector (i,r,t) is defined to describe the current state of the vision system and each possible state corresponds to a subset of rules to deal with it. The recognition and location task can be described as a process of rule calling and state conversions. The most suitable rule is selected at each step to try to acquire more useful information as soon as possible. Experiments are shown in the paper.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"58 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":"121663938","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
Constraint-fusion for interpretation of articulated objects 解释铰接对象的约束融合
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323808
Y. Hel-Or, M. Werman
{"title":"Constraint-fusion for interpretation of articulated objects","authors":"Y. Hel-Or, M. Werman","doi":"10.1109/CVPR.1994.323808","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323808","url":null,"abstract":"This paper presents a method for interpretation of modeled objects that is general enough to cover articulated and other types of constrained models. The flexibility between components of the model are expressed as spatial constraints which are fused into the pose estimation during the interpretation process. The constraint fusion assists in obtaining the correct interpretation and in reducing the search of possible correspondences. The proposed method can handle any constraint (including inequalities) between any number of different components of the model. The framework is based on Kalman filtering.<<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":"122597037","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: 16
Age classification from facial images 面部图像的年龄分类
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323894
Y. Kwon, N. Lobo
{"title":"Age classification from facial images","authors":"Y. Kwon, N. Lobo","doi":"10.1109/CVPR.1994.323894","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323894","url":null,"abstract":"The ability to classify age from a facial image has not been pursued in computer vision. This research addresses the limited task of age classification of a facial image into a baby, young adult, and senior adult. This is the first reported work to classify age, and to successfully extract and use natural wrinkles. We present a theory and practical computations for visual age classification from facial images, based on cranio-facial changes in feature-position ratios, and on skin wrinkle analysis. Three age groups are classified.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"61 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":"124766762","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: 816
Hexagonal wavelet representations for recognizing complex annotations 用于识别复杂注释的六边形小波表示
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323890
A. Laine, S. Schuler
{"title":"Hexagonal wavelet representations for recognizing complex annotations","authors":"A. Laine, S. Schuler","doi":"10.1109/CVPR.1994.323890","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323890","url":null,"abstract":"This paper describes a method of pattern recognition targeted for recognizing complex annotations found in paper documents. Our investigation is motivated by the high reliability required for accomplishing autonomous interpretation of maps and engineering drawings. Our approach includes a strategy based on multiscale representations obtained by hexagonal wavelet analysis. A feasibility study is described in which more than 10,000 patterns were recognized with an error rate of 2.06% by a neural network trained using multiscale representations from a class of 52 distinct patterns. We observed a 21-fold reduction in the amount of information needed to represent each pattern for recognition. These results suggest that high reliability is possible at a reduced cost of representation.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"28 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":"122165978","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: 47
A visual-motion fixation invariant 一个视觉运动固定不变量
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323828
D. Raviv, N. Ozery
{"title":"A visual-motion fixation invariant","authors":"D. Raviv, N. Ozery","doi":"10.1109/CVPR.1994.323828","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323828","url":null,"abstract":"The paper deals with a visual-motion fixation invariant. We show that during fixation there is a measurable nonlinear function of optical flow that produces the same value for all points of a stationary environment, regardless of the 3D shape of the environment. During fixated camera motion relative to a rigid object, e.g., a stationary environment, the projection of the fixated point remains (by definition) at the same location in the image, and all other points located on the 3D rigid object can only rotate relative to the 3D fixation point. This rotation rate of the points is invariant for all points that lie on the particular environment, and it is measurable from a sequence of images. This new invariant is obtained from a set of monocular images, and is expressed explicitly as a closed form solution. We show how to extract this invariant analytically from a sequence of images using optical flow information, and we present results obtained from real data experiments.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"53 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":"131370184","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
Determination of motion parameters and estimation of point correspondences in small nonrigid deformations 小非刚性变形中运动参数的确定和点对应的估计
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323930
C. Kambhamettu, Dmitry Goldgof, M. He
{"title":"Determination of motion parameters and estimation of point correspondences in small nonrigid deformations","authors":"C. Kambhamettu, Dmitry Goldgof, M. He","doi":"10.1109/CVPR.1994.323930","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323930","url":null,"abstract":"Recovery of motion parameters and point correspondences is a fundamental problem in computer vision. Although a great deal of research has been done in solving rigid motion, nonrigid motion analysis has only recently been addressed and is gaining interest due to its wide range of applications. This paper introduces a novel method for estimating motion parameters and point correspondences between surfaces under small nonrigid deformations. It uses the changes in differential geometric properties of surface under motion. Simulations are performed by generating nonrigid motion on an ellipsoidal data to illustrate performance and accuracy of derived algorithms, Then, the algorithm is tested on the sequence of facial range images. The motion parameters generated by the algorithm has also been used do detect the abnormality in cardiac images.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"141 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":"124711249","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: 28
Site model supported monitoring of aerial images 站点模型支持航拍图像的监测
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323776
C. L. Lin, Q. Zheng, R. Chellappa, L. Davis, Xiaopeng Zhang
{"title":"Site model supported monitoring of aerial images","authors":"C. L. Lin, Q. Zheng, R. Chellappa, L. Davis, Xiaopeng Zhang","doi":"10.1109/CVPR.1994.323776","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323776","url":null,"abstract":"Image monitoring, the process of locating and identifying significant changes or new activities, is one of the most important imagery exploitation tasks. A site model supported image monitoring system which utilizes image understanding techniques driven by an underlying site model is presented. In our approach, we first register the image to be monitored to an existing site model, which is constructed using the RADIUS Common Development Environment; the regions of interest are then delineated based on site information, camera acquisition parameters, and goals of the image analyst; object extraction is then done using constraints on size, shape, orientation, and shadow of the target object derived from known information about image resolution, 3-D shape of the object, camera viewing and illuminant directions. The results of object detection are used for monitoring changes.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"6 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":"121471511","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: 21
A shape-from-texture algorithm based on human visual psychophysics 基于人类视觉心理物理学的形状-纹理算法
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323877
K. Sakai, L. Finkel
{"title":"A shape-from-texture algorithm based on human visual psychophysics","authors":"K. Sakai, L. Finkel","doi":"10.1109/CVPR.1994.323877","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323877","url":null,"abstract":"We propose an algorithm for the determination of three dimensional shape and perspective based on the response of the human visual system to changes in visual textures. Current computer vision algorithms are computationally intensive and show inherent difficulties in integrating additional cues for the determination of shape, such as shading, contour, or motion. In order to develop a fast and simple mechanism less constrained for integrating other cues, we incorporated aspects of the physiological properties of cortical cells in VI into a network model. We provide psychophysical evidence that the local spatial frequency spectrum is represented by the spatially averaged peak frequency (APF). After normalization, this APF measures texture compression and leads to estimates of 3D shape and depth. Simulations of the model show good agreement with human responses to a range of textured images.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"47 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":"120964100","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
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