People tracking by fusing different kinds of sensors, floor sensors and acceleration sensors

To realize accurate tracking of people in the environment, many studies have been proposed using vision sensors, floor sensors, and wearable devices. Floor sensors can reliably detect current positions, but it is difficult to estimate correct associations between observations and multiple people. To solve the problem, we propose to combine acceleration sensors that are attached to the human body. Since the signals from floor sensors and acceleration sensors synchronize when they observe same person walking, these signals are not independent. The synchrony between the signals is evaluated based on statistical test to find correct association. People tracking examples are shown to confirm the effectiveness of the proposed method. Significant improvement in correct association rate is achieved compared to the results only by floor sensors