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Proceedings Paper

Geometric measurement of moving object based on visual detecting-learning mechanism
Author(s): Hong Wang; Jia Deng
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Paper Abstract

This paper proposes a novel geometric statistical measurement of long sequence moving objects, which can accurately measure the geometry of the moving objects in non-contact measurement environment. The proposed algorithm adopts detecting-learning method for tracking moving objects in a long-term, gets the moving sequence data, extracts the geometric contour and computes the geometric and motion parameters of the objects. Then we analyze the long sequence to train the parameters. Experimental data showed that the adoption of geometric measurement of moving objects based on detecting-learning mechanism performs favorably. The method can provide high-accuracy geometric and motion parameters of the objects.

Paper Details

Date Published: 19 February 2015
PDF: 4 pages
Proc. SPIE 9449, The International Conference on Photonics and Optical Engineering (icPOE 2014), 94493A (19 February 2015); doi: 10.1117/12.2083096
Show Author Affiliations
Hong Wang, Sichuan Normal Univ. (China)
Jia Deng, Sichuan Normal Univ. (China)


Published in SPIE Proceedings Vol. 9449:
The International Conference on Photonics and Optical Engineering (icPOE 2014)
Ailing Tian; Anand Asundi; Weiguo Liu; Chunmin Zhang, Editor(s)

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