3-1 0 Adaptive Background Estimation for Object Tracking
Ryunosuke Itoh, Yoshio Iwai, Masahiko Yachida · 2002
Tracking people has received considerable attention by computer vision researchers. Interest is motivated by the broad range of potential applications such as personal identification, human-machine interaction, and automated surveillance. We previously proposed a method for extracting moving region by subtraction from background images. Background images were estimated by using UD factorized Kalman Filter. In order to use a Kalman Filter, good initial parameters are needed for estimation and were manually given in the previous work. In this paper we propose an improved method for estimation of background image and for automatic parameter initialization. We also show experimental results using real images to test the performance of our proposed method.