Compensation algorithm for optical flow vectors based on image sequences of the spot

Yuhua Zhao; Feng Yuan

doi:10.1117/12.865913

11 October 2010 Compensation algorithm for optical flow vectors based on image sequences of the spot

Yuhua Zhao; Feng Yuan

Author Affiliations +

Proceedings Volume 7656, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment; 76562K (2010) https://doi.org/10.1117/12.865913
Event: 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies, 2010, Dalian, China

Abstract

A key problem in the processing of image sequences is estimating the motion between video frames, often referred to as optical flow estimation. For the problem of the target spots loss in image sequences when aircraft's 3D attitude parameters is measured based on optical measurement, an effective optical flow vectors compensation algorithm from multi-frames image is proposed. First, the optical flow vectors between frames of spot target image sequences are calculated by Lucas-Kanade algorithm, and then choose the optical flow vectors nearby the images of lost spot target. The chosen vectors are used for estimating spot image. The compensation model of optical flow vectors is set. Then, the lost spot target center is got by using inverse distance weighted averaging and the weight-value is the difference of the frame count between real image and estimated image. By experiments analysis, the proper calculating scope of this arithmetic under the expected precision is determined. This algorithm compensates the calculation errors caused by the lost target in image sequences efficiently.

Citation Download Citation

Yuhua Zhao, Yuhua Zhao, Feng Yuan, Feng Yuan, } "Compensation algorithm for optical flow vectors based on image sequences of the spot", Proc. SPIE 7656, 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 76562K (11 October 2010); doi: 10.1117/12.865913; https://doi.org/10.1117/12.865913

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