ORIGINAL ARTICLE K. Morioka (*) Meiji University, 1-1-1 Higashimita, Tama-ku, Kawasaki, Kanagawa 214-8571, Japan Tel. +81-44-934-7304; Fax +81-44-934-7304 e-mail: {morioka,leejooho,h.hashimoto}@ieee.org J.-H. Lee Ritsumeikan University, Shiga, Japan Y. Kuroda · H. Hashimoto IIS, University of Tokyo, Tokyo, Japan Artif Life Robotics (2007) 11:204–210 © ISAROB 2007 DOI 10.1007/s10015-007-0429-9 Kazuyuki Morioka · Joo-Ho Lee · Yoichi Kuroda Hideki Hashimoto Hybrid tracking based on color histogram for intelligent space in the environment, such as in a house, factory, hospital, etc. We have proposed the concept of Intelligent Space (iSpace) 5 in order to achieve human-centered services by accelerating both physical and psychological interactions between humans and their environment. The iSpace is con- structed with CCD-camera-based intelligent sensors, which include a processing and networking capacity. These intel- ligent sensors are called Distributed Intelligent Network Devices (DINDs). Positional estimations of humans and mobile robots based on the tracking of a color marker, 6 human behavior recognition, 7 and control of mobile robots which supporting humans 8,9 has been achieved in the iSpace. The most important task of the sensing infrastructure in the iSpace is object tracking and the localization of moving objects. The object tracking system in the iSpace can be considered as a multi-camera multi-object tracking system. There are two major problems in the multiple-camera multiple-object tracking system. The first is the traditional correspondence problem from frame to frame over time in the image sequence. The second is the object correspon- dence problem among different cameras in order to achieve seamless tracking. This article focuses on the first problem. In the research field of object tracking, one challenging task is how to deal with the rapid movements of the object. A method using partial background information which does not use all the image information, such as background sub- traction, is presented. The benefit of using background- weighted histograms is described in the article by Comaniciu et al. 10 In this method, a background area which is three times the size of the target area is extracted in every frame. Using two histograms representing the extended back- ground area, the features of the target object are increased and the tracking capability is improved. In the article by Nummiaro et al., 11 a robust object tracker for a fast-moving object is proposed. In this method, a hundred samples of partial background areas are extracted in advance, and object tracking is implemented using a particle filter. Trackers based on background information are useful for Abstract The vision sensor network is expected to achieve a contact-free wide-area location system without any addi- tional burden on users in intelligent environments. In this article, a tracking algorithm for a location system in an intelligent environment is described. A modified color tracker based on a Kalman filter and a mean shift procedure is proposed in order to improve the robustness for occlusion and rapid movement. To handle the sudden change in object movement, we propose a hybrid tracking algorithm, including an adaptive feedback loop, based on the statistics of color histogram models after the mean-shift process. Experimental results showed that the proposed method achieves more robust tracking of multiple objects than the conventional method. Key words Intelligent space · Color histogram · Kalman filter · Hybrid tracking 1 Introduction The research field on intelligent environments including many ubiquitous devices such as computers and sensors, has recently been expanding. 1,2 Some intelligent environments utilize a distributed vision sensor network as a sensing infra- structure. 3,4 Vision sensor networks achieve a contact-free wide-area location system without any additional burden to users. It also has the capacity to obtain further information depending on the image processing. Distributed vision sensor networks offer promising prospects as the infrastruc- ture for robots which are required to coexist with humans Received: December 15, 2006 / Accepted: April 16, 2007