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14 May 2012Evaluation of image collection requirements for 3D reconstruction using phototourism techniques on sparse overhead data
Phototourism is a burgeoning field that uses collections of ground-based photographs to construct a three-dimensional
model of a tourist site, using computer vision techniques. These techniques capitalize on the extensive overlap generated
by the various visitor-acquired images from which a three-dimensional point cloud can be generated. From there, a
facetized version of the structure can be created. Remotely sensed data tends to focus on nadir or near nadir imagery
while trying to minimize overlap in order to achieve the greatest ground coverage possible during a data collection. A
workflow is being developed at Digital Imaging and Remote Sensing (DIRS) Group at the Rochester Institute of
Technology (RIT) that utilizes these phototourism techniques, which typically use dense coverage of a small object or
region, and applies them to remotely sensed imagery, which involves sparse data coverage of a large area. In addition
to this, RIT has planned and executed a high-overlap image collection, using the RIT WASP system, to study the
requirements needed for such three-dimensional reconstruction efforts. While the collection was extensive, the intention
was to find the minimum number of images and frame overlap needed to generate quality point clouds. This paper will
discuss the image data collection effort and what it means to generate and evaluate a quality point cloud for
reconstruction purposes.
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Erin Ontiveros, Carl Salvaggio, David Nilosek, Nina Raqueño, Jason Faulring, "Evaluation of image collection requirements for 3D reconstruction using phototourism techniques on sparse overhead data," Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83900K (14 May 2012); https://doi.org/10.1117/12.919319