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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01g445cd252
Title: Texture Synthesis-Based Hole Filling for LiDAR Data
Authors: Dai, Angela
Advisors: Funkhouser, Tom
Department: Computer Science
Class Year: 2013
Abstract: Light Detection and Ranging (LiDAR) scanning to produce 3D point cloud data inherently results in holes in the data due to both opaque foreground objects and transparent objects seen from only a single point of view. However, it does not suffice to simply fill the holes by interpolating the boundaries, as this produces blatant loss of structure. We present a texture synthesis-based approach to synthesizing data to fill in missing geometric data based upon the existing geometric data, and demonstrate its efficacy on large scale data sets of point cloud data of cities from the Google StreetView mapping project.
Extent: 38 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01g445cd252
Access Restrictions: Walk-in Access. This thesis can only be viewed on computer terminals at the Mudd Manuscript Library.
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Computer Science, 1988-2016

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