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Title:Predicting object occupancy on the floor from RGBD images of indoor scenes
Author(s):Bhobe, Sujay
Advisor(s):Hoiem, Derek W.
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):object occupancy
graph cuts
alpha expansion
label prediction
overhead view
scene understanding
computer vision
Abstract:This thesis presents an approach to predict the occupied area on the floor in an image of an indoor scene. The goal is to be able to obtain navigable areas even in cluttered indoor environments. This algorithm could be used in the field of robotics where robots need to navigate through a room while being mindful of the surrounding objects. The results are quite close to the ground truth, as exemplified by the false positive, false negative, precision and recall rates. Using this algorithm improves the label predictions.
Issue Date:2013-05-24
URI:http://hdl.handle.net/2142/44195
Rights Information:Copyright 2013 Sujay Uday Bhobe
Date Available in IDEALS:2013-05-24
Date Deposited:2013-05


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