3-D Model-Based Tracking for UAV Indoor Localization

• Published in: IEEE transactions on cybernetics Vol. 45; no. 5; pp. 869 - 879
• Main Authors: Teuliere, Celine, Marchand, Eric, Eck, Laurent
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2015
• Subjects: Aircraft; Algorithms; Cameras; Clustering algorithms; Computer Simulation; Image edge detection; Image Interpretation, Computer-Assisted - methods; Imaging, Three-Dimensional - methods; Minimization; Model-based tracking; Models, Statistical; Navigation; particle filtering; Pattern Recognition, Automated - methods; Robotics - methods; Robustness; Solid modeling; Subtraction Technique; UAV application; UAV application; particle filtering; Model-based tracking
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2014.2337652

This paper proposes a novel model-based tracking approach for 3-D localization. One main difficulty of standard model-based approach lies in the presence of low-level ambiguities between different edges. In this paper, given a 3-D model of the edges of the environment, we derive a multiple hypotheses tracker which retrieves the potential poses of the camera from the observations in the image. We also show how these candidate poses can be integrated into a particle filtering framework to guide the particle set toward the peaks of the distribution. Motivated by the UAV indoor localization problem where GPS signal is not available, we validate the algorithm on real image sequences from UAV flights.