A Hybrid Method for Visitor Localization and Tracking in a Museum Environment
Ching-Chun Huang, Hoang Tran Vu, Hung Nguyen Manh, Wei-Chi Chang, Wei-Yuan Lin, Hung-Sheng Cheng and Yi-Ning Chuang
The proposed framework for visitor localization
In this paper, we developed a localization system using smart glasses for museum environments. By taking advantage of the existing QR (Quick Response) codes which are deployed for embedding artwork information in a museum, we proposed a hybrid method using Inertial Measurement Unit (IMU), camera, and Wi-Fi radio signal for visitor localization and tracking. The IMU could provide direct self-motion information for target tracking; however, its measurements might not be robust owing to error propagation from gyro and acceleration biases. Thus, in this paper, a vision system was introduced as a complementary part for localization refinement. Concretely, we utilized smart glasses to detect the existing QR code and based on camera geometry to infer the relative target location by reference to the QR code position. Next, a Kalman Filter (KF) framework was used to derive the coarse location of a visitor by combining the IMU measurements and the vision-based localization result. Finally, the region around the coarse location was treated as a region of interest (ROI) for a Wi-Fi positioning system. Based on the radio signal strength indicator (RSSI) and the trained radio map within the ROI, the visitor location was inferred by applying a K-nearest neighbor (KNN) algorithm. The experiment results show the efficiency of our method compared with an IMU-based method, a Wi-Fi-based method, and an IMU and Wi-Fi fusion method.
The layout of the testing environment
The step detection result. Red lines represent the thresholds
Results of our experiments using different methods