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

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Geometric heat equation and nonlinear diffusion of shapes and images 几何热方程和形状和图像的非线性扩散
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323817
B. Kimia, Kaleem Siddiqi
{"title":"Geometric heat equation and nonlinear diffusion of shapes and images","authors":"B. Kimia, Kaleem Siddiqi","doi":"10.1109/CVPR.1994.323817","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323817","url":null,"abstract":"We propose a geometric smoothing method based on local curvature in shapes and images which is governed by the geometric heat equation and is a special case of the reaction-diffusion framework proposed by Faugeras (1990). For shapes, the approach is analogous to the classical heat equation smoothing, but with a renormalization by arc-length at each infinitesimal step. For images, the smoothing is similar to anisotropic diffusion in that, since the component of diffusion in the direction of the brightness gradient is nil, edge location and sharpness are left intact. We present several properties of curvature deformation smoothing of shape: it preserves inclusion order, annihilates extrema and inflection points without creating new ones, decreases total curvature, satisfies the semi-group property allowing for local iterative computations, etc. Curvature deformation smoothing of an image is based on viewing it as a collection of iso-intensity level sets, each of which is smoothed by curvature and then reassembled. This is shown to be mathematically sound and applicable to medical, aerial and range images.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"25 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":"114705213","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: 151
Extraction of the zero-crossings of the curvature derivatives in volumic 3D medical images: a multi-scale approach 体三维医学图像曲率导数的零交叉提取:一种多尺度方法
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323912
O. Monga, R. Lengagne, R. Deriche
{"title":"Extraction of the zero-crossings of the curvature derivatives in volumic 3D medical images: a multi-scale approach","authors":"O. Monga, R. Lengagne, R. Deriche","doi":"10.1109/CVPR.1994.323912","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323912","url":null,"abstract":"Recently, we have shown that the differential properties of the surfaces represented by 3D volumic images can be recovered using their partial derivatives. For instance, the crest lines can be characterized by the first, second and third partial derivatives of the grey level function I(x, y, z). In this paper, we show that: the computation of the partial derivatives of an image can be improved using recursive filters which approximate the Gaussian filter; a multi-scale approach solves many of the instability problems arising from the computation of the partial derivatives; and we illustrate the previous point for the crest line extraction (a crest point is a zero-crossing of the derivative of the maximum curvature along the maximum curvature direction). We present experimental results of crest point extraction on real 3-D medical data.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"53 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120819866","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
Document image understanding: geometric and logical layout 文档图像理解:几何和逻辑布局
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323855
R. Haralick
{"title":"Document image understanding: geometric and logical layout","authors":"R. Haralick","doi":"10.1109/CVPR.1994.323855","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323855","url":null,"abstract":"Document image understanding encompasses the technology required to make paper documents equivalent to other computer exchange media like floppies, tapes, and CDROMs. The physical reader of the paper document is the scanner just like the physical reader of the floppy is the floppy drive and the physical reader of the tape cartridge is the tape cartridge drive, and the physical reader of the CDROM is the CDROM drive. In the survey presented, we restrict ourselves to documents such as business letters, forms, and scientific and technical articles such as those found in archival journals and technical conferences. Understanding such documents involves estimating the rotation skew of each document page, determining the geometric page layout, labeling blocks as text or non-text, determining the read order for text blocks, recognizing the text of text blocks through an OCR system, determining the logical page layout, and formatting the data and information of the document in a suitable way for use by a word processing system or by an information retrieval system.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"622 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":"123951293","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: 146
Occluding contour detection using affine invariants and purposive viewpoint control 基于仿射不变量和目标视点控制的遮挡轮廓检测
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323847
Kiriakos N. Kutulakos, C. Dyer
{"title":"Occluding contour detection using affine invariants and purposive viewpoint control","authors":"Kiriakos N. Kutulakos, C. Dyer","doi":"10.1109/CVPR.1994.323847","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323847","url":null,"abstract":"We present an approach for identifying the occluding contour and determining its sidedness using an active (i.e., moving) observer. It is based on the non-stationarity property of the visible rim: When the observer's viewpoint is changed, the visible rim is a collection of curves that \"slide,\" rigidly or non-rigidly over the surface. We show that the absenter can deterministically choose three views on the tangent plane of selected surface points to distinguish such curves from stationary surface curves (i.e., surface markings). Our approach demonstrates that the occluding contour can be identified directly, i.e., without first computing surface shape (distance and curvature).<<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":"130047785","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: 23
Skeleton-space: a multiscale shape description combining region and boundary information 骨架空间:结合区域和边界信息的多尺度形状描述
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323891
R. Ogniewicz
{"title":"Skeleton-space: a multiscale shape description combining region and boundary information","authors":"R. Ogniewicz","doi":"10.1109/CVPR.1994.323891","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323891","url":null,"abstract":"A multiscale extension to the medial axis transform(MAT) or skeleton can be obtained by combining information derived from a scale-space hierarchy of boundary representations with region information provided by the MAT. The skeleton-space is constructed by attributing each skeleton component with a hierarchically ordered sequence of residual values, each expressing the saliency of the component at a distinct resolution level. Since our method amounts to a rather symbolic than iconic computation of a multiscale MAT, it does not introduce the correspondence problem between distinct levels of detail, in contrast to other commonly proposed techniques. Our multiscale MAT is capable of describing complex shapes characterized by significantly jagged boundaries. Furthermore, tracking the evolution of prominent loci of the MAT such as nodes across scales permits to assess the most significant skeleton constituents and to automatically determine pruning parameters. A salient subset of the MAT (first order skeleton) can be extracted without the need of manual threshold adjustment.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"60 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":"132509180","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: 99
Detecting multiple image motions by exploiting temporal coherence of apparent motion 利用视运动的时间相干性检测多重图像运动
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323921
Hsiao-Jing Chen, Y. Shirai
{"title":"Detecting multiple image motions by exploiting temporal coherence of apparent motion","authors":"Hsiao-Jing Chen, Y. Shirai","doi":"10.1109/CVPR.1994.323921","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323921","url":null,"abstract":"Motion-based image segmentation becomes inherently ambiguous when apparent motions of different objects are locally or globally similar during a period. To disambiguate the segmentation, temporal coherence between the local image motion at each edge point and the apparent motion of every object is examined over a long sequence. The point is grouped into that segment of the object whose apparent motion is temporally most coherent with the local image motion at the point.<<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":"130603024","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
Probe based recognition of targets in infrared images 基于探针的红外图像目标识别
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323916
S. Der, R. Chellappa
{"title":"Probe based recognition of targets in infrared images","authors":"S. Der, R. Chellappa","doi":"10.1109/CVPR.1994.323916","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323916","url":null,"abstract":"A probe based approach is presented for the recognition of targets in a cluttered background using an infrared imager. A probe is a simple mathematical function which operates locally on image grey levels and produces an output that is more directly usable by an algorithm. A directional probe image is calculated by taking the difference in grey levels between pixels a set distance apart in a given direction, centered on the probe image pixel. A parametric statistical image background model which describes the probe images is introduced. The parameters of the probe image model can be readily estimated from the image. Knowledge of these parameters, together with target signatures obtained from Computer Aided Design (CAD) models, allows the likelihood ratio for a given object pose hypothesis versus the background null hypothesis to be written. The generalized likelihood ratio test is used to accept one of the object poses or to choose the null hypothesis. Results of the method applied to a large set of terrain model board images are presented.<<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":"130408009","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: 4
Time and space efficient pose clustering 时间和空间有效的姿态聚类
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323837
C. Olson
{"title":"Time and space efficient pose clustering","authors":"C. Olson","doi":"10.1109/CVPR.1994.323837","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323837","url":null,"abstract":"This paper shows that the pose clustering method of object recognition can be decomposed into small sub-problems without loss of accuracy. Randomization can then be used to limit the number of sub-problems that need to be examined to achieve accurate recognition. These techniques are used to decrease the computational complexity of pose clustering. The clustering step is formulated as an efficient tree search of the pose space. This method requires little memory since not many poses are clustered at a time. Analysis shows that pose clustering is not inherently more sensitive to noise than other methods of generating hypotheses. Finally, experiments on real and synthetic data are presented.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"30 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":"126493982","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: 29
Structure from image sequences captured through a monocular extra-wide angle lens 结构从图像序列捕获通过单眼超广角镜头
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323925
K. Kato, Tadashi Nakanishi, A. Shio, K. Ishii
{"title":"Structure from image sequences captured through a monocular extra-wide angle lens","authors":"K. Kato, Tadashi Nakanishi, A. Shio, K. Ishii","doi":"10.1109/CVPR.1994.323925","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323925","url":null,"abstract":"This paper presents a new method for extracting the 3-D shape and texture of an object undergoing translational motion from image sequences captured through a monocular extra-wide picture viewing angle. The feature of this work is extracting this information from image sequences without requiring rigid environmental conditions. In this method, the relative positions between target and view position are estimated based on spatio-temporal image analysis, and shape is reconstructed from the multiple silhouette information. After reconstructing the 3-D shape, the voxel value of a surface point is determined by statistically analyzing those images that contain the surface point. The proposed method can extract 3-D shape and surface texture at a stroke from outdoor scenes. An experiment using real outdoor scenes confirms the effectiveness of the method.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"51 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120922696","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
Surface curvature from integrability 曲面曲率的可积性
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Pub Date : 1994-06-21 DOI: 10.1109/CVPR.1994.323876
J. Fan, L. B. Wolff
{"title":"Surface curvature from integrability","authors":"J. Fan, L. B. Wolff","doi":"10.1109/CVPR.1994.323876","DOIUrl":"https://doi.org/10.1109/CVPR.1994.323876","url":null,"abstract":"We present a multiple illumination technique that directly recovers the viewer-centered curvature matrix up to a scalar factor, at each mutually illuminated point on a smooth object surface. This technique is completely independent of knowledge of incident illumination orientation, local surface orientation, or diffuse surface albedo. The cornerstone of this technique is the use of the integrability constraint which is a fundamental mathematical property of smooth surfaces. The integrability constraint allows the derivation of an equation at each object point, which is linear in terms of quantities involving the initially unknown parameters of incident illumination orientation. These quantities, which we call the gradient ratio constants, can be simultaneously solved for from five or more equations arising from the same number of object points. We show that deriving these gradient ratio constants provides just enough calibration information about incident illumination geometry to compute the viewer-centered curvature matrix at each object point, up to a scalar multiple. We demonstrate two important applications of this technique: segmentation of the object surface by sign of Gaussian curvature, and further segmentation of non-negative Gaussian curvature into convexity and concavity.<<ETX>>","PeriodicalId":160667,"journal":{"name":"1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","volume":"65 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":"121210109","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
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