University of Illinois Urbana-Champaign

Predicting object occupancy on the floor from RGBD images of indoor scenes

Bhobe, Sujay

Content Files
Bhobe_Sujay_MSThesis_Files.zip
Sujay_Bhobe.pdf

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https://hdl.handle.net/2142/44195

Description

Title
Predicting object occupancy on the floor from RGBD images of indoor scenes
Author(s)
Bhobe, Sujay
Issue Date
2013-05-24T21:53:54Z
Director of Research (if dissertation) or Advisor (if thesis)
Hoiem, Derek W.
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2013-05-24T21:53:54Z
Keyword(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.
Graduation Semester
2013-05
Permalink
http://hdl.handle.net/2142/44195
Copyright and License Information
Copyright 2013 Sujay Uday Bhobe

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