{"title":"Stability of phase information","authors":"David J. Fleet, A. Jepson","doi":"10.1109/WVM.1991.212788","DOIUrl":"https://doi.org/10.1109/WVM.1991.212788","url":null,"abstract":"This paper concerns the robustness of phase information for measuring image velocity and binocular disparity, its stability with respect to geometric deformations, and its linearity as a function of spatial position. These properties are shown to depend on the form of the filters used and their frequency bandwidths. The authors also discuss situations in which phase is unstable, many of which can be detected using the model of phase singularities (see Image Vis. Comput. (UK) vol.9, no.5, p.333-7 (Oct. 1991)).<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114662911","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}
{"title":"Robustness of structure from binocular known motion","authors":"R. Dutta, M. A. Snyder","doi":"10.1109/WVM.1991.212784","DOIUrl":"https://doi.org/10.1109/WVM.1991.212784","url":null,"abstract":"The paper analyses the important issues associated with structure computations through binocular motion when inertial navigation systems are used to find the sensor motion parameters. In particular, the authors study the conditions under which the relative error in environmental depth is reduced through the use of binocular motion over the separate use of monocular motion and static stereo. The results obtained give lower bounds on relative errors in depth. Examples on typical situations are included to illustrate their theoretical conclusions.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134584729","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}
{"title":"Recovering a boundary-level structural description from dynamic stereo","authors":"A. P. Tirumalai, B. G. Schunck, R. Jain","doi":"10.1109/WVM.1991.212786","DOIUrl":"https://doi.org/10.1109/WVM.1991.212786","url":null,"abstract":"The authors present a stereo algorithm to recursively compute a boundary-level structural description of a scene, from a sequence of stereo images. This algorithm utilizes connected line segments as the basic match primitive, which yields a description composed primary of boundaries of objects in the scene. A description of this nature is very useful for obstacle avoidance and path planning for mobile robots. The stereo matching algorithm is integrated into a dynamic stereo vision system to compute and incrementally refine such a structural description recursively, using belief functions. The approach is illustrated with a real dynamic stereo sequence acquired from a mobile robot.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123545589","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}
{"title":"Recursive estimation of shape and nonrigid motion","authors":"D. Metaxes, Demetri Terzopoulos","doi":"10.1109/WVM.1991.212770","DOIUrl":"https://doi.org/10.1109/WVM.1991.212770","url":null,"abstract":"The authors paper presents an approach for recursively estimating 3D object shape and general nonrigid motion, which makes use of physically based dynamic models. The models provide global deformation parameters which represent the salient shape features of natural parts, and local deformation parameters which capture shape details. The equations of motion governing the models, augmented by point-to-point constraints, make them responsive to externally applied forces. The authors extend this system of differential equations to formulate a shape and nonrigid motion estimator, a nonlinear Kalman filter, that recursively transforms the discrepancy between the data and the estimated model state into generalized forces while formally accounting for uncertainty in the observations. A Riccati update process maintains a covariance matrix that adjusts the forces in accordance with the system dynamics and the current and prior observations. The estimator applies the transformed forces to adjust the translational, rotational, and deformational degrees of freedom such that the model evolves as consistently as possible with the noisy data. The authors present model fitting and motion tracking experiments of articulated flexible objects from real and synthetic noise-corrupted 3D data.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128864351","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}
{"title":"Direct estimation of time-to-impact from optical flow","authors":"M. Tistarelli, G. Sandini","doi":"10.1109/WVM.1991.212803","DOIUrl":"https://doi.org/10.1109/WVM.1991.212803","url":null,"abstract":"The estimation of time to impact is of vital importance for animals as well as for autonomous robots. The optical flow is used to estimate the time to impact. The authors demonstrate that the motion equations that relate the egomotion and/or the motion of the objects in the scene to the optical flow are considerably simplified if the velocity is represented in a polar or log-polar coordinate system, as opposed to a Cartesian representation. In the former case, the time-to-impact can be directly computed from the velocity field and its derivatives. The analysis takes place considering a tracking egomotion, but is then generalized to arbitrary sensor and object motion. The main result stems from the abundance of equations that can be written directly relating the optical flow, represented in a polar or log-polar coordinate system, with the time-to-impact. Experiments performed on images acquired from real scenes are presented.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126271319","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}
{"title":"Principle of superposition: a common computational framework for analysis of multiple motion","authors":"M. Shizawa, K. Mase","doi":"10.1109/WVM.1991.212811","DOIUrl":"https://doi.org/10.1109/WVM.1991.212811","url":null,"abstract":"The principle of superposition is applied to various motion estimation problems. It can potentially resolve the difficulty of analyzing multiple motion, transparent motion and motion boundaries by using a common mathematical structure. The authors demonstrate that, by applying the principle, the techniques of optical flow, 3D motion and structure from flow fields, direct method for 3D motion and structure recovery, motion and structure from correspondences in two frames can be extended coherently to deal with multiple motion. The theory not only produces multiple-motion versions of the existing algorithms, but also provides tools for the theoretical analysis of multiple motion. Since the approach is not at the algorithm level as are conventional segmentation paradigms, but at the level of computational theory, i.e. of constraints, theoretical results derived also contribute to psychophysical and physiological studies on the preattentive stages of biological motion vision systems. The paper emphasizes the universality of the principle.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124491076","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}
{"title":"Motion recovery from image sequences using First-order optical flow information","authors":"S. Negahdaripour, S. Lee","doi":"10.1109/WVM.1991.212778","DOIUrl":"https://doi.org/10.1109/WVM.1991.212778","url":null,"abstract":"A closed-form solution for motion estimation from first-order flow in two 'distinct' image regions is described. Uniqueness is guaranteed when these correspond to surface patches with different normal vectors. given an image sequence, the authors show how the image many be segmented into regions with the necessary properties, optical flow is computed for these regions, and motion parameters are computed. The method can be applied to arbitrary scenes and camera motion. The authors explain why it is more robust than other techniques that require the knowledge of the full flow or information up to the second-order terms of it. Experimental results are presented to support the theoretical derivations.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132560688","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}
{"title":"Recovering observer translation with center-surround operators","authors":"D. Heeger, A. Jepson, Eero P. Simoncelli","doi":"10.1109/WVM.1991.212782","DOIUrl":"https://doi.org/10.1109/WVM.1991.212782","url":null,"abstract":"The optical flow field for an observer moving through a static environment depends on the observer's translational and rotational motion along with the distances to each surface point. The authors previously introduced 'subspace methods' for recovering 3D motion and depth from optical flow. These methods solve first for the observer's translation, independent of rotation and depth. The authors discuss a particular implementation of this general theory, utilizing 'center-surround motion-opponent operators' that prefer motion in one direction in the center and motion in the opposite direction in the surround. Cells in visual area MT of the primate brain are known to have velocity-selective receptive fields with a similar center-surround spatial organization. The authors propose a theoretical framework for analyzing MT cell responses.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132021492","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}
{"title":"Motion and structure from long stereo image sequences","authors":"Ning Cui, J. Weng, P. Cohen","doi":"10.1109/WVM.1991.212785","DOIUrl":"https://doi.org/10.1109/WVM.1991.212785","url":null,"abstract":"The treatment of uncertainty in 3D points determined by stereo triangulation affects significantly the reliability of the estimated 3D motion and structure. The authors first address this issue in the estimation of inter-frame motion. Two methods are discussed, a closed-form matrix-weighted least-squares solution and an iterative optimal solution. Using each of these two methods for two-view analyses, the authors proceed to deal with long image sequences. A recursive-batch approach is adopted to fuse multiple stereo views in order to achieve higher performance without suffering from excessive computational cost. Experiments with a real stereo image sequence have been presented to show the performance of the algorithms.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124768914","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}
{"title":"Towards structure from motion for linear features through reference points","authors":"Long Quan, R. Mohr","doi":"10.1109/WVM.1991.212800","DOIUrl":"https://doi.org/10.1109/WVM.1991.212800","url":null,"abstract":"The 3D reconstruction from projections and feature correspondence between projections are two major problems in structure from motion. The authors show a geometric method on how a 3D affine shape is obtained from two parallel projections through general 4 reference points, or from two central projections when additional vanishing points are available. And they show also that correspondences can be established through reference points; the reference points configuration for central projections should contain at least a set of 4 coplanar points. The method is developed both for point and line segment features. Apart from that the correspondence of the necessary reference points should be known in advance, one needs neither to calibrate cameras nor to have any knowledge of its position and displacement. Projective geometry and affine geometry invariants are manipulated to perform both reconstruction and correspondence.<<ETX>>","PeriodicalId":208481,"journal":{"name":"Proceedings of the IEEE Workshop on Visual Motion","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1991-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129415117","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}