Online 3-D trajectory estimation of a flying object from a monocular image sequence

Authors:
R. Herrejon;S. Kagami;K. Hashimoto
Affiliations:
Intelligent Control Systems Laboratory at the Department of System Information Sciences of Tohoku University, Sendai, Japan;Intelligent Control Systems Laboratory at the Department of System Information Sciences of Tohoku University, Sendai, Japan;Intelligent Control Systems Laboratory at the Department of System Information Sciences of Tohoku University, Sendai, Japan
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

The problem considered here involves the design and application of a recursive algorithm to extract and predict the position of an object in a 3D environment from one feature correspondence from a monocular image sequence. Translational model involves an object moving in a parabolic path using projectile physics. A state-space model is constructed incorporating kinematic states, and recursive techniques are used to estimate the state vector as a function of time. The measured data are the noisy image plane coordinates of object match taken from image in the sequence. Image plane noise levels are allowed and investigated. The problem is formulated as a tracking problem, which can use an arbitrary large number of images in a sequence. The recursive estimation is done using Recursive Least Squares (RLS). Results on both synthetic and real imagery illustrate the performance of the estimator.