Premium
Robust estimation of 3D trajectories from a monocular image sequence
Author(s) -
Pang ChungYi Chan,
Guesalaga Andrés R.,
Roda Valentín Obac
Publication year - 2002
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.10020
Subject(s) - artificial intelligence , computer vision , computer science , translation (biology) , monocular , a priori and a posteriori , kalman filter , sequence (biology) , fundamental matrix (linear differential equation) , rotation (mathematics) , trajectory , image plane , image (mathematics) , mathematics , mathematical analysis , biochemistry , chemistry , philosophy , genetics , physics , epistemology , astronomy , biology , messenger rna , gene
This article describes a new method for object trajectory estimation that uses sequences of images taken from a monocular camera. The method integrates a Kalman filter to estimate the three‐dimensional (3D) parameters of the optical system and a lineal projective model to determine 3D point coordinates projected on the retinal plane. It works with at least three distinctive points in the image, and they are updated with correlation methods. The result is an estimation of the rotation and translation parameters between successive images within the sequence and yield to the 3D coordinates of the points selected for correspondence. The scaling problem related to 3D reconstruction is tackled via a priori information of the objects being observed. The method is tested with synthetic images to evaluate its accuracy, and later, an interesting application in autonomous navigation is presented. © 2002 Wiley Periodicals, Inc. Int J Imaging Syst Technol 12, 128–137, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.10020