Adaptive Background Estimation for Object Tracking

2 Adaptive Background Model 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-machineinteraction,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 parametersare 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 experimentalresults using real images to test the performance of our proposed method.

• Type: Journal
• Year: 2002
• Where: MVA
• Authors: Ryunosuke Itoh, Yoshio Iwai, Masahiko Yachida
• Keywords: Adaptive Background Model, Background Image, Computer Vision, Kalman Filter, MVA 2002