We propose a multi-pedestrian tracking system based on MEMS based IMUs as a novel tool for human behavior analysis. With asynchronized multiple IMUs, our system can track IMU-attached pedestrians in synchronization at a high frame rate in the large environment, compared with vision based approaches. The output data is similar to standard PDR systems as follows: the time-series position, velocity, and heading of the pedestrians in the 3D space. To realize our system, we propose a simple but effective calibration technique for synchronizing the timelines of the asynchronized IMUs. With our system, users can analyze the detailed motion behaviors of the people who participate in a group work or a collective activity, quantitatively. By combining with other sensors such as an eye tracker, our system can further provide more comprehensive data in the experiments.
|Number of pages||8|
|Journal||CEUR Workshop Proceedings|
|Publication status||Published - Jan 1 2019|
|Event||Short Paper of the 10th International Conference on Indoor Positioning and Indoor Navigation - Work-in-Progress Papers, IPIN-WiP 2019 - Pisa, Italy|
Duration: Sep 30 2019 → Oct 3 2019
All Science Journal Classification (ASJC) codes
- Computer Science(all)