Gait Matching by Mapping Wearable to Camera Privacy-Preserving Recordings: Experimental Comparison of Multiple Settings

This work concerns a gait matching problem. An experimental simulation of people walking in an interior area, some of which had wearables with accelerometer and gyroscope, and some of which were recorded by some camera set up in this area, was conducted. From all devices data from single-point vectors were acquired, thus preserving privacy. The aim was to match each person carrying a wearable with the correct camera recording, if this recording existed, or not to match the person with any camera recording, if it was not recorded by a camera for sufficient time. For this matching, deliberately chosen pairs of wearable and camera features were correlated after state-of-the-art-based automatic synchronization, and the correlation matrices resulting from the feature pairs, after rationally transformed to improve results, were fused with the best linear combination. From the experiments, perfect matching results were obtained when the time series to be compared lasted at least 50sec, no matter any other assumption.