Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223248
W. Niblack, Phillip B. Gibbons, D. Capson
An algorithm for generating skeletons of objects in a binary image is described. The algorithm produces a well-centered skeleton with the same simple connectivity as the object, and it allows the object to be either exactly or approximately (to within a known, user-selectable error) reconstructed. Its connectivity and reconstructability properties can be rigorously proved. For approximate reconstruction, the skeleton can also be (almost always) thin and is insensitive to border noise without image prefiltering or skeleton post-pruning, while maintaining the precise error bounds for reconstruction. Because of these properties, its robustness to rotation, pleasing visual appearance, and flexibility, it is well suited for such applications as data compression, image analysis, character recognition, and circuit board inspection.<>
{"title":"Generating connected skeletons for exact and approximate reconstruction","authors":"W. Niblack, Phillip B. Gibbons, D. Capson","doi":"10.1109/CVPR.1992.223248","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223248","url":null,"abstract":"An algorithm for generating skeletons of objects in a binary image is described. The algorithm produces a well-centered skeleton with the same simple connectivity as the object, and it allows the object to be either exactly or approximately (to within a known, user-selectable error) reconstructed. Its connectivity and reconstructability properties can be rigorously proved. For approximate reconstruction, the skeleton can also be (almost always) thin and is insensitive to border noise without image prefiltering or skeleton post-pruning, while maintaining the precise error bounds for reconstruction. Because of these properties, its robustness to rotation, pleasing visual appearance, and flexibility, it is well suited for such applications as data compression, image analysis, character recognition, and circuit board inspection.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115087815","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223180
U. R. Dhond, J. Aggarwal
Contemporary stereo correspondence algorithms disambiguate multiple candidate matches by using a spatial hierarchy mechanism. Narrow occluding objects in 3-D scenes cannot be handled by the spatial hierarchy mechanism alone. The authors propose a dynamic disparity search (DDS) framework that combines the spatial hierarchy mechanism with a new disparity hierarchy mechanism, to reduce the stereo matching errors caused by narrow occluding objects. They demonstrate the merits of the DDS approach on real stereo images.<>
{"title":"Computing stereo correspondences in the presence of narrow occluding objects","authors":"U. R. Dhond, J. Aggarwal","doi":"10.1109/CVPR.1992.223180","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223180","url":null,"abstract":"Contemporary stereo correspondence algorithms disambiguate multiple candidate matches by using a spatial hierarchy mechanism. Narrow occluding objects in 3-D scenes cannot be handled by the spatial hierarchy mechanism alone. The authors propose a dynamic disparity search (DDS) framework that combines the spatial hierarchy mechanism with a new disparity hierarchy mechanism, to reduce the stereo matching errors caused by narrow occluding objects. They demonstrate the merits of the DDS approach on real stereo images.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114179859","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223240
J. Vlontzos, D. Geiger
A Markov random field (MRF) formulation for the problem of optical flow computation is studied. An adaptive window matching scheme is used to obtain a good measure of the correlation between the two images. A confidence measure for each match is also used. Thus, the input to the system is the adaptive correlation and the corresponding confidence. The MRF model is then used to estimate the velocity field and the velocity discontinuities. The problem of occlusions is addressed, and a relationship between occlusions and motion discontinuities is established.<>
{"title":"A MRF approach to optical flow estimation","authors":"J. Vlontzos, D. Geiger","doi":"10.1109/CVPR.1992.223240","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223240","url":null,"abstract":"A Markov random field (MRF) formulation for the problem of optical flow computation is studied. An adaptive window matching scheme is used to obtain a good measure of the correlation between the two images. A confidence measure for each match is also used. Thus, the input to the system is the adaptive correlation and the corresponding confidence. The MRF model is then used to estimate the velocity field and the velocity discontinuities. The problem of occlusions is addressed, and a relationship between occlusions and motion discontinuities is established.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115928566","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223221
H. Beyer
A basic review of the bundle adjustment with self-calibration is given. The mathematical model, parameter estimation, and quality analysis of calibration and positioning are covered. The calibration procedure, hardware, and testfield of an accuracy investigation with off-the-shelf CCD (charge-coupled device) camera, lens, and frame grabber are described. A relative accuracy in object space of 1 part in 30000 and an accuracy of 1/45 in image space were verified by independent measurements with theodolites.<>
{"title":"Accurate calibration of CCD-cameras","authors":"H. Beyer","doi":"10.1109/CVPR.1992.223221","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223221","url":null,"abstract":"A basic review of the bundle adjustment with self-calibration is given. The mathematical model, parameter estimation, and quality analysis of calibration and positioning are covered. The calibration procedure, hardware, and testfield of an accuracy investigation with off-the-shelf CCD (charge-coupled device) camera, lens, and frame grabber are described. A relative accuracy in object space of 1 part in 30000 and an accuracy of 1/45 in image space were verified by independent measurements with theodolites.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123128563","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223186
M. Swain, R. E. Kahn, D. Ballard
The high-resolution field of view of the human eye only covers a tiny fraction of the total field of view, which allows for great economy in computational resources but forces the visual system to solve other problems that would not exist with uniformly high resolution. One of these is how to determine where to redirect the fovea, given only the low-resolution information available in the periphery. The advent of spatially variant receptor arrays for cameras has made it imperative that computational solutions to this problem be found. Color has been traditionally associated with foveal vision, but it is shown that color cues are well preserved under low resolution, and an algorithm for locating objects based on color histograms that is both effective under low resolution and computationally efficient is illustrated.<>
{"title":"Low resolution cues for guiding saccadic eye movements","authors":"M. Swain, R. E. Kahn, D. Ballard","doi":"10.1109/CVPR.1992.223186","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223186","url":null,"abstract":"The high-resolution field of view of the human eye only covers a tiny fraction of the total field of view, which allows for great economy in computational resources but forces the visual system to solve other problems that would not exist with uniformly high resolution. One of these is how to determine where to redirect the fovea, given only the low-resolution information available in the periphery. The advent of spatially variant receptor arrays for cameras has made it imperative that computational solutions to this problem be found. Color has been traditionally associated with foveal vision, but it is shown that color cues are well preserved under low resolution, and an algorithm for locating objects based on color histograms that is both effective under low resolution and computationally efficient is illustrated.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126209375","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223200
P. Sajda, L. Finkel
The problems of object segmentation and binding are addressed within a biologically based network model capable of determining depth from occlusion. In particular, the authors discuss two subprocesses most relevant to segmentation and binding: contour binding and figure direction. They propose that these two subprocesses have intrinsic constraints that allow several underdetermined problems in occlusion processing and object segmentation to be uniquely solved. Simulations that demonstrate the role these subprocesses play in discriminating objects and stratifying them in depth are reported. The network is tested on illusory stimuli, with the network's response indicating the existence of robust psychological properties in the system.<>
{"title":"Object segmentation and binding within a biologically-based neural network model of depth-from-occlusion","authors":"P. Sajda, L. Finkel","doi":"10.1109/CVPR.1992.223200","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223200","url":null,"abstract":"The problems of object segmentation and binding are addressed within a biologically based network model capable of determining depth from occlusion. In particular, the authors discuss two subprocesses most relevant to segmentation and binding: contour binding and figure direction. They propose that these two subprocesses have intrinsic constraints that allow several underdetermined problems in occlusion processing and object segmentation to be uniquely solved. Simulations that demonstrate the role these subprocesses play in discriminating objects and stratifying them in depth are reported. The network is tested on illusory stimuli, with the network's response indicating the existence of robust psychological properties in the system.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129793518","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223265
J. Dolan, E. Riseman
A computational framework for computing curvilinear structure on the edge data of images is presented. The method is symbolic, operating on geometric entities/tokens. It is also constructive, hierarchical, parallel, and locally distributed. Computation proceeds independently at each token and at each stage interleaves the discovery of structure with its careful description. The process yields a hierarchy of descriptions at multiple scales. These multiscale descriptions provide efficient feature indexing both for the grouping process itself as well as for subsequent recognition processes. Experimental results are presented to demonstrate the effectiveness of the approach with respect to curvilinear structure, and its application to more general grouping problems is discussed.<>
{"title":"Computing curvilinear structure by token-based grouping","authors":"J. Dolan, E. Riseman","doi":"10.1109/CVPR.1992.223265","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223265","url":null,"abstract":"A computational framework for computing curvilinear structure on the edge data of images is presented. The method is symbolic, operating on geometric entities/tokens. It is also constructive, hierarchical, parallel, and locally distributed. Computation proceeds independently at each token and at each stage interleaves the discovery of structure with its careful description. The process yields a hierarchy of descriptions at multiple scales. These multiscale descriptions provide efficient feature indexing both for the grouping process itself as well as for subsequent recognition processes. Experimental results are presented to demonstrate the effectiveness of the approach with respect to curvilinear structure, and its application to more general grouping problems is discussed.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124794144","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223234
J. Hervé, Y. Aloimonos
An active approach to the integration of shape from x modules-here shape from shading and shape from texture-is proposed. The question of what constitutes a good motion for the active observer is addressed. Generally, the role of the visual system is to provide depth information to an autonomous robot; a trajectory module will then interpret it to determine a motion for the robot, which in turn will affect the visual information received. It is suggested that the motion can also be chosen so as to improve the performance of the visual system.<>
{"title":"Exploratory active vision: theory","authors":"J. Hervé, Y. Aloimonos","doi":"10.1109/CVPR.1992.223234","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223234","url":null,"abstract":"An active approach to the integration of shape from x modules-here shape from shading and shape from texture-is proposed. The question of what constitutes a good motion for the active observer is addressed. Generally, the role of the visual system is to provide depth information to an autonomous robot; a trajectory module will then interpret it to determine a motion for the robot, which in turn will affect the visual information received. It is suggested that the motion can also be chosen so as to improve the performance of the visual system.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131100753","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223212
K. Ikeuchi, T. Suehiro
A novel method for programming a robot, called the assembly-plan-from-observation (APO) method, is proposed. The APO method aims to build a system that has the capability of observing a human performing an assembly task, understanding the task based on the observation, and generating the robot program to achieve the same task. Assembly relations that serve as the basic representation of each assembly task are defined. It is verified that such assembly relations can be recovered from the observation of human assembly tasks, and that from such assembly relations it is possible to generate robot motion commands to repeat the same assembly task. An APO system based on the assembly relations is demonstrated.<>
{"title":"Recognizing assembly tasks using face-contact relations","authors":"K. Ikeuchi, T. Suehiro","doi":"10.1109/CVPR.1992.223212","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223212","url":null,"abstract":"A novel method for programming a robot, called the assembly-plan-from-observation (APO) method, is proposed. The APO method aims to build a system that has the capability of observing a human performing an assembly task, understanding the task based on the observation, and generating the robot program to achieve the same task. Assembly relations that serve as the basic representation of each assembly task are defined. It is verified that such assembly relations can be recovered from the observation of human assembly tasks, and that from such assembly relations it is possible to generate robot motion commands to repeat the same assembly task. An APO system based on the assembly relations is demonstrated.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126982291","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}
Pub Date : 1992-06-15DOI: 10.1109/CVPR.1992.223260
B. Super, A. Bovik
A closed-form solution to the problem of computing 3D curved-surface shape from texture cues is presented. An expression showing the dependence of localized image spectral moments on localized surface spectral moments and on local surface orientation is derived. The local image spectra are measured with wavelets, and the expression is solved for the surface orientation at each point. Because the method uses localized spectral information, it operates at a very low level in the visual hierarchy. No extraction of texture or edge elements is required. The wavelet-based computation used is biologically plausible, easily parallelized for rapid computation, and has been shown to be the basis for effective solutions to a variety of other vision tasks. The method is demonstrated on a number of real-world examples.<>
{"title":"Shape-from-texture by wavelet-based measurement of local spectral moments","authors":"B. Super, A. Bovik","doi":"10.1109/CVPR.1992.223260","DOIUrl":"https://doi.org/10.1109/CVPR.1992.223260","url":null,"abstract":"A closed-form solution to the problem of computing 3D curved-surface shape from texture cues is presented. An expression showing the dependence of localized image spectral moments on localized surface spectral moments and on local surface orientation is derived. The local image spectra are measured with wavelets, and the expression is solved for the surface orientation at each point. Because the method uses localized spectral information, it operates at a very low level in the visual hierarchy. No extraction of texture or edge elements is required. The wavelet-based computation used is biologically plausible, easily parallelized for rapid computation, and has been shown to be the basis for effective solutions to a variety of other vision tasks. The method is demonstrated on a number of real-world examples.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126754128","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}
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