Analyzing networks of static and dynamic geospatial entities for urban situational awareness

Sherrill, D.M.; Yee, Michael; Cho, Peter

doi:10.1117/12.818174

Cited by 1 publication

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“…Each photo corresponds to a node in the graph, and edges link images with matching SIFT features. The image graph for 1012 Manhattan photos is shown in Figure 2, using a graph layout and interactive rendering tool developed by M. Yee [7]. For this particular set of 1000+ photos, the graph divides roughly into two large clusters, representing the Manhattan skyline and the Statue of Liberty.…”

Section: D Photo Reconsturctionmentioning

confidence: 99%

3D exploitation of large urban photo archives

2010

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Recent work in computer vision has demonstrated the potential to automatically recover camera and scene geometry from large collections of uncooperatively-collected photos. At the same time, aerial ladar and Geographic Information System (GIS) data are becoming more readily accessible. In this paper, we present a system for fusing these data sources in order to transfer 3D and GIS information into outdoor urban imagery. Applying this system to 1000+ pictures shot of the lower Manhattan skyline and the Statue of Liberty, we present two proof-of-concept examples of geometrybased photo enhancement which are difficult to perform via conventional image processing: feature annotation and image-based querying. In these examples, high-level knowledge projects from 3D world-space into georegistered 2D image planes and/or propagates between different photos. Such automatic capabilities lay the groundwork for future real-time labeling of imagery shot in complex city environments by mobile smart phones.

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Section: D Photo Reconsturctionmentioning

confidence: 99%