{"title":"Computing consistent normals and colors from photometric data","authors":"H. Rushmeier, F. Bernardini","doi":"10.1109/IM.1999.805339","DOIUrl":"https://doi.org/10.1109/IM.1999.805339","url":null,"abstract":"We present a method for computing normals and colors from multiple sets of photometric data that are consistent with each other and an underlying lower resolution mesh. Normals are computed by locally adjusting the light source intensities using data from the underlying mesh. Colors are derived from the photometric calculations, and are adjusted by a global color registration, analogous to global geometric registration.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117335612","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":"Dense disparity estimation using Gabor filters and image derivatives","authors":"M. Ouali, C. Laurgeau, D. Ziou","doi":"10.1109/IM.1999.805380","DOIUrl":"https://doi.org/10.1109/IM.1999.805380","url":null,"abstract":"We tackle the recurrent problem of disparity estimation since the mapping from disparity to depth is well understood while the automatic disparity extraction is still subject to errors. We propose to use the image derivatives with the phase-based approach to overcome the tuning problem of the filter. Moreover we propose a quadratic model for the singularities neighborhood detection. The approach is characterized by the simplicity of its implementation. It also provides dense and accurate disparity maps. A numerical error analysis shows that the results are very satisfactory.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682360","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":"Estimating pose through local geometry","authors":"G. Soucy, F. Callari, F. Ferrie","doi":"10.1109/IM.1999.805352","DOIUrl":"https://doi.org/10.1109/IM.1999.805352","url":null,"abstract":"The problem of estimating and tracking the pose of a 3D object is a well-established problem in machine vision with important applications in terrestrial and space robotics. The paper describes how 3D range data, available from a new generation of real time laser rangefinding systems, can be used to solve the pose determination problem. The approach is based on analysis of the local geometric structure encoded in the range data to extract landmarks. Local configurations of these landmarks provide estimates of identity and pose through matching against a nominal model using a Bayesian optimization technique. Aggregates of local estimates are used to provide a robust estimate of global pose. The technique is well suited to space tracking applications for which examples are provided.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128664671","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":"Automatic feature correspondence for scene reconstruction","authors":"Philip W. Smith, Mark D. Elstrom","doi":"10.1109/IM.1999.805378","DOIUrl":"https://doi.org/10.1109/IM.1999.805378","url":null,"abstract":"To construct complete three-dimensional representations from multiple range images or to employ color images as texture maps for surface models, the relative positions of the sensors used to capture the data must be known. Most data-driven methods for pose estimation require either an accurate initial estimation of the relative orientation be specified or a corresponding set of features be extracted from images. The autonomous identification of corresponding feature positions thus represents the major difficulty in creating completely automated registration and reconstruction systems that place no restrictions on relative sensor positions. In this paper, an automated feature correspondence technique, specifically designed for the task of multi-modal view registration is presented which requires no initial pose estimates or geometric matching constraints. Both photo-realistic and 3-D scene models are presented that were constructed autonomously by systems employing the described matching algorithm.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116979109","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":"Dynamic gaze-controlled levels of detail of polygonal objects in 3-D environment modeling","authors":"H. Zha, Y. Makimoto, T. Hasegawa","doi":"10.1109/IM.1999.805362","DOIUrl":"https://doi.org/10.1109/IM.1999.805362","url":null,"abstract":"We present a new method for controlling levels of detail (LODs) of triangulated polygonal objects by a gaze-driven approach. The method relies upon a hierarchical mesh representation we call a merge-and-split tree (MST) of vertices, in which objects are described at nearly continuous LODs. The idea behind the LOD control is to adjust the mesh shape quality adaptively under a geometrical definition of gaze points and fovea regions. Not only does it generate a circular fovea region with smooth transition of LODs, but it also makes possible a real time updating of the whole mesh for moving gaze. We have applied our LOD control technique to several large models, and the results show that the method is effective in revealing high details in a fovea region guided by a gaze point moving freely across 3D surfaces.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124125486","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":"Moving objects detection from time-varied background: an application of camera 3D motion analysis","authors":"Zhencheng Hu, K. Uchimura","doi":"10.1109/IM.1999.805334","DOIUrl":"https://doi.org/10.1109/IM.1999.805334","url":null,"abstract":"Motion detection from a moving observer is a very important technique for 3D dynamical image analysis. Because of continuous background variations, detecting real moving objects has become very difficult and employs an optical flow method to measure the flow vector difference between the background and moving objects. Unfortunately, there is a huge calculation cost for obtaining accurate optical flow vectors. A new motion detecting method based on camera 3D motion analysis is proposed. With the special motion features of an on-board camera and FOE, our method can detect real moving objects simply by matching two adjacent frames. The camera 3D motion can theoretically be determined in our method with only three matching pairs, which makes it fast and more efficient for real-time applications.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123648013","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":"Computations on a spherical view space for efficient planning of viewpoints in 3-D object modeling","authors":"K. Morooka, H. Zha, T. Hasegawa","doi":"10.1109/IM.1999.805344","DOIUrl":"https://doi.org/10.1109/IM.1999.805344","url":null,"abstract":"Viewpoint planning plays an important role in automatic 3D model generation. Previously (H, Zha et al., 1997), we proposed a viewpoint planning method to determine the next-best-viewpoint (NBV) for incremental model construction. Based on a current partial model, this algorithm provides quantitative evaluations on the suitability of viewpoints as the NBV. Since the evaluation is performed for all potential viewpoints, the NBV planning is very time-consuming. We present a novel method of discretizing a spherical view space by a look-up array which will highly facilitate the NBV evaluations. Two main issues are addressed: 1) a uniform tessellation of the spherical space and its mapping onto the 2D array; 2) incremental updating computations far evaluating viewpoints as the NBV. The efficiency of the method is verified by algorithmic analyses and experiments using a real modeling system.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122551573","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":"A geometric approach to the segmentation of range images","authors":"M. Bock, C. Guerra","doi":"10.1109/IM.1999.805356","DOIUrl":"https://doi.org/10.1109/IM.1999.805356","url":null,"abstract":"We present a novel geometric approach to extract planes from sets of 3D points. For a set with n points the algorithm has an O(n/sup 3/ log n) time complexity. We also discuss an implementation of the algorithm for range image segmentation. The performance of the new range image segmentation algorithm is compared to other existing methods.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125261250","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":"Efficient and reliable template set matching for 3D object recognition","authors":"M. Greenspan, P. Boulanger","doi":"10.1109/IM.1999.805353","DOIUrl":"https://doi.org/10.1109/IM.1999.805353","url":null,"abstract":"Object recognition in range image data is formulated as template set matching. The object model is represented as a set of voxel templates, one for each possible pose. The set of all templates is composed into a binary decision tree. Each leaf node references a small number of templates. Each internal node references a single voxel, and has two branches, T and F. The subtree branching from the T branch contains the subset of templates which contain the node voxel. Conversely, the subtree branching from F branch contains the subset of templates which do not contain the node voxel. Traversing the tree at any image location executes a point probe strategy. It efficiently determines a good match with the template set by interrogating only those elements which discriminate between the remaining possible interpretations. The method has been implemented for a number of different heuristic tree design and traversal methods. Results are presented of extensive tests for two objects under isolated, cluttered, and occluded scene conditions. It is shown that there exist traversal/design combinations which are both efficient and reliable, and that the method is robust.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126823757","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":"Curve and surface models to drive 3D reconstruction using stereo and shading","authors":"D. Roussel, P. Bourdot, R. Gherbi","doi":"10.1109/IM.1999.805337","DOIUrl":"https://doi.org/10.1109/IM.1999.805337","url":null,"abstract":"We propose a reconstruction technique which consists in defining a parametric surface lying on a closed curve by setting the extremal behavior of the surface along the curve on which it lies. Therefore, we most build a set of curves in space from a stereo reconstruction of matched and closed contours in an image pair. Then, we use photometric information extracted near the image contours to define the local behavior of the surfaces lying on the closed curves. In order to build such a surface we use the duality existing between a stereo-based reconstruction which is able to determine the position of points in the scene space and photoclinometry which gives information about the shape of the objects in the scene. Our geometric model is composed of a radial set of triparametric Gregory patches for each surface to reconstruct. The topological concepts introduced by these kind of surfaces and the use of photometric models gave a framework for both image analysis processing and reconstruction geometrical processing.","PeriodicalId":110347,"journal":{"name":"Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121754200","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}