Geometric measurement of moving object based on visual detecting-learning mechanism
Hong Wang, Jia Jun Deng · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
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.