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" Comprehensive three dimensional change detection using volumetric appearance modeling "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 53851
Doc. No : TL23805
Call number : ‭3377189‬
Main Entry : Thomas B. Pollard
Title & Author : Comprehensive three dimensional change detection using volumetric appearance modeling\ Thomas B. Pollard
College : Brown University
Date : 2009
Degree : Ph.D.
student score : 2009
Page No : 135
Abstract : The problem of detecting changes in images taken by a stationary camera has been well studied and many algorithms now exist which perform robustly in real-world applications. However no comprehensive solution exists for the analogous "3-d" change detection problem, where the camera taking the images is allowed to move and the scene is not planar. This situation is common in a growing number of applications, especially in aerial surveillance where the recent explosion of available aerial imagery has made manual examination by analysts infeasible. This thesis presents the first comprehensive solution to the 3-d change detection problem, using a new framework called volumetric appearance modeling (VAM). This approach can manage the complications of unknown and sometimes changing world surfaces by maintaining a 3-d voxel-based model, where probability distributions for surface occupancy and image appearance are stored in each voxel. These distributions are continuously updated as new images are received using an adaptive learning procedure. VAM is demonstrated to perform well on several aerial image sequences taken from helicopter from a wide range of viewpoints. The core VAM framework is extended to additionally deal with the variable lighting and haze conditions present in satellite imagery. The success of this complete framework is demonstrated on selected scenes of Baghdad, Iraq exhibiting a challenging range of viewpoints, lighting directions, and haze.
Subject : Applied sciences; Change detection; Volumetric appearance; Aerial surveillance; Computer vision; Electrical engineering; Artificial intelligence; Computer science; 0984:Computer science; 0544:Electrical engineering; 0800:Artificial intelligence
Added Entry : J. L. Mundy
Added Entry : Brown University
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