@inproceedings{1dea6b9838a74b0bb07d03ff4a09d55f,
title = "Microsoft kinect sens{\"o}r{\"u} kullanarak zemin d{\"u}zlemi algilama",
abstract = "Ground plane detection is essential for successful navigation of vision based mobile robots. We introduce a novel and robust ground plane detection algorithm using depth information acquired by a Kinect sensor. Unlike similar methods from the literature, we do not assume that the ground plane covers the largest area in the scene. Furthermore our algorithm handles two different conditions: fixed and changing view angle of the sensor. We show that the algorithm is robust if the view angle is fixed whereas an additional procedure handles different view angles satisfactorily.",
keywords = "Autonomous robot navigation, Depth map, Ground plane detection, Microsoft kinect, Mobile robots, Obstacle detection",
author = "Dogan Kircali and Tek, \{F. Boray\} and Iyidir, \{Ibrahim K.\}",
year = "2013",
doi = "10.1109/SIU.2013.6531356",
language = "T{\"u}rk{\c c}e",
isbn = "9781467355629",
series = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013",
booktitle = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013",
note = "2013 21st Signal Processing and Communications Applications Conference, SIU 2013 ; Conference date: 24-04-2013 Through 26-04-2013",
}