Indoor pedestrian trajectory tracking based on activity recognition

Abstract

Indoor location services (LBSs) have attracted a great deal of attention in recent years, the user's indoor trajectories play an important role in LBSs. In this paper, we combine pedestrian dead reckoning (PDR), human activity recognition (HAR) and landmarks to achieve a good accuracy for indoor localization. The core idea of our research is using PDR to estimate the user's location, and the cumulative error of PDR is reduced by landmarks, which sensed by HAR. In addition, we use step-based classification method to improve the activity recognition accuracy, and we use a magnetometer to aid in identifying door opening activities. The experimental results show that our method can achieve a high degree of accuracy for indoor pedestrian trajectory tracking.