People tracking by cross modal association of vision sensors and acceleration sensors

Abstract

To realize accurate tracking of people in the environment, many studies have been proposed using vision sensors, floor sensors, and wearable devices. The problem of using vision sensors is that they do not provide ID information of each people and there are ambiguities when people come across. To solve the problem, we propose to combine acceleration sensors that are attached to the human body. Since the signals from vision sensors and acceleration sensors synchronize when they observe same person who are acting or walking in the environment, these signals are not independent. The correlation between the signals is evaluated based on the canonical correlation analysis. Experimental results are shown to detect gesture and to track people to confirm the effectiveness of the proposed method.