DocumentCode :
50580
Title :
Stereo Reconstruction of Droplet Flight Trajectories
Author :
Zarrabeitia, Luis A. ; Qureshi, Faisal Z. ; Aruliah, Dhavide A.
Author_Institution :
Fac. of Sci., Univ. of Ontario Inst. of Technol., Oshawa, ON, Canada
Volume :
37
Issue :
4
fYear :
2015
fDate :
April 1 2015
Firstpage :
847
Lastpage :
861
Abstract :
We developed a new method for extracting 3D flight trajectories of droplets using high-speed stereo capture. We noticed that traditional multi-camera tracking techniques fare poorly on our problem, in part due to the fact that all droplets have very similar shapes, sizes and appearances. Our method uses local motion models to track individual droplets in each frame. 2D tracks are used to learn a global, non-linear motion model, which in turn can be used to estimate the 3D locations of individual droplets even when these are not visible in any camera. We have evaluated the proposed method on both synthetic and real data and our method is able to reconstruct 3D flight trajectories of hundreds of droplets. The proposed technique solves for both the 3D trajectory of a droplet and its motion model concomitantly, and we have found it to be superior to 3D reconstruction via triangulation. Furthermore, the learned global motion model allows us to relax the simultaneity assumptions of stereo camera systems. Our results suggest that, even when full stereo information is available, our unsynchronized reconstruction using the global motion model can significantly improve the 3D estimation accuracy.
Keywords :
computer vision; feature extraction; image motion analysis; learning (artificial intelligence); object tracking; stereo image processing; 3D flight trajectory extraction; 3D flight trajectory reconstruction; high-speed stereo capture; learning; local motion models; multicamera tracking technique; stereo camera system; stereo information; stereo reconstruction; Aerodynamics; Cameras; Image reconstruction; Target tracking; Three-dimensional displays; Trajectory; Stereo reconstruction; multi-target tracking; multi-view geometry; nonlinear motion; parameter estimation;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2014.2353638
Filename :
6888516
Link To Document :
بازگشت