A Practical Approach To Creating Precise And Detailed 3d Models From Single And Multiple Views

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ConferenceProceedings of the XIX ISPRS Congress, July 16-23, 2000., Amsterdam, Holland
Subjectimage registration; modeling; multi-sensor; scanner; segmentation; surface reconstruction; VR; modélisation; multicapteur; scanner; segmentation; reconstruction de surfaces; réalité virtuelle (RV)
AbstractThis paper describes a general system for creating geometrically correct and complete 3D models of objects and environments. The main process uses digital images and applies rigorous photogrammetric techniques. Once the images are registered using bundle adjustment, points in selected locations are measured in all the images where they appear. However, there are usually many parts of the scene that appear in only one image due to occlusions or lack of features. These parts can be reconstructed in the 3D space from the coordinates in a single image and the mathematical model of the surface determined by fitting a function to existing surface points. This produces a sampled geometry in the form of points in the three-dimensional space however the connectivity or the topology is not known and must be determined someway. The proposed approach relies on interactive point segmentation and automatic triangulation. Counting on images for modeling is limited because the features that can be extracted are usually fewer then the required level of details. To overcome this problem two options are implemented. First, large number of points can be automatically added to surfaces of known shape, such as spheres, cylinders and quadrics, using a polygon subdivision method. The second option integrates data from range sensors that can densely digitize the surface where filled out details are required. The presented approach will be assessed by several examples representing various types of objects and sites.
Publication date
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number43655
NPARC number8913593
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Record identifier654813a9-7747-406d-83f5-172410790be5
Record created2009-04-22
Record modified2016-05-09
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