Sparse Line-Optical Flow Field Computing Method Based on Lines Matching

Abstract:

This paper brings out a new sparse line-optical flow field computing method. Firstly, we establish a lines matching algorithm based on Kalman Filter (KF). In this algorithm, we map lines in an image into Hough space, after that we employ KF to predict the position in the following frame in order to match lines in image sequence. Secondly, we present the concept of sparse line-optical flow field of images and propose the calculation method of it. By using the camera perspective projection model and the optical flow Identity, we can get the sparse line-optical flow field. Simulations is made in the following step, and results show that the lines matching algorithm works well and the accuracy of the calculation method proposed in this paper is as good as that of the classic Horn algorithm, while the calculating time-cost of it is only 1/30 Horn algorithms.

• Periodical: Applied Mechanics and Materials (Volumes 496-500)
• Pages: 2099-2107
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.496-500.2099
• Online since: January 2014
• Authors: Zhen Yu Guan*, Jie Li, Huan Yang
• Keywords: Camera Perspective Projection Model, Kalman Filter (KF), Lines Matching, Sparse Line-Optical Flow Field

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