Iterated model-based estimation of object pose using kalman filter with an active camera

In this paper, we propose the novel method for estimating the three dimensional position and pose of the object by using only one active camera. Our method estimates the depth length from the camera to the object by a Kalman filter. Kalman filter enables the depth distance estimation with high accuracy by using one camera and decreases the number of the iteration by estimating the accurate depth distance. Moreover, we iterate the estimation by updated input images. Although the distance from a camera to the object was about 600mm, the experimental results showed that the estimated error of the depth length was about 2.4mm.