Estimation of Object Position And Movement by Bayesian Inference

Abstract

A method of measuring the position and movement of an object in a non-contact manner using Bayesian inference is considered. The position and movement of an object can be measured by processing the movement of the object captured as a moving image by image recognition by Bayesian inference. Since it can produce features different from those of conventional measurement methods, it can be applied in various ways. This paper describes the development of basic theories and algorithms for that purpose. Bayesian inference can provide learning and inference that is completely different from neural networks. Therefore, it may be possible to overcome the problems of neural networks.