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3D Scanning Using Consumer-Grade Depth Sensors: Methods and Applications

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dc.contributor.advisor Samaras, Dimitris en_US
dc.contributor.author Orrego, Carlos en_US
dc.contributor.other Department of Computer Science en_US
dc.date.accessioned 2013-05-22T17:35:21Z
dc.date.accessioned 2015-04-24T14:47:12Z
dc.date.available 2013-05-22T17:35:21Z
dc.date.available 2015-04-24T14:47:12Z
dc.date.issued 2012-05-01
dc.identifier Orrego_grad.sunysb_0771M_10956 en_US
dc.identifier.uri http://hdl.handle.net/1951/59813 en_US
dc.identifier.uri http://hdl.handle.net/11401/71366 en_US
dc.description 55 pg. en_US
dc.description.abstract A 3D scanner is a device that analyzes a real world object and generates a point cloud describing the surface of such object, possibly including color information as well. However, these devices are expensive, fragile, large, and usually require especially adapted facilities to house them. The advent of inexpensive depth sensors such as Kinect provide new opportunities to bridge the existing gap between systems that offer good scanning quality and systems that are affordable. The objective of this thesis is to use Kinect as a 3D scanner. We achieve this goal by exploring techniques to generate point clouds from depth maps, and triangulation methods to construct meshes from point clouds. However, depth maps are not noise-free. To deal with this noise, we explore different depth map reconstruction and smoothing techniques. We then measure their effectiveness in reducing the noise and enhancing the quality of the generated model. The main contribution of this work is an acquisition and processing pipeline that allows for capture and generation of accurate 3D models whose quality is comparable to those generated by expensive scanner devices. We show that the accuracy of our acquisition system is on par with higher resolution scanners. We also demonstrate applications for our method by capturing a data set of human faces and generating an Active Appearance Model from this data set. en_US
dc.description.sponsorship This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree. en_US
dc.format Monograph en_US
dc.format.medium Electronic Resource en_US
dc.language.iso en_US en_US
dc.publisher The Graduate School, Stony Brook University: Stony Brook, NY. en_US
dc.subject.lcsh Computer science en_US
dc.subject.other 3D reconstruction, AAM, Kinect en_US
dc.title 3D Scanning Using Consumer-Grade Depth Sensors: Methods and Applications en_US
dc.type Thesis en_US
dc.mimetype Application/PDF en_US
dc.contributor.committeemember Gu, Xianfeng en_US
dc.contributor.committeemember Berg, Tamara. en_US


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