Abstract
For the past decade, running simulators or video games have become popular to complement indoor sports practice. These applications require at least one running and a display device such as a smartphone and another interaction device that receives and communicates the player’s movements to the application. For treadmill running, the most commonly used interaction devices are smartwatches or pedometers that adapt to the conditions and particularities of the activity without significantly interfering with the running dynamics. In this sense, to determine if there are alternatives that avoid auxiliary interactive devices, this paper presents a method to estimate the runner’s cadence by facial tracking. The proposed technique uses the smartphone camera to capture, analyze and estimate the runner’s movement. The results obtained and the comparison with data collected with other sensors support face-tracking techniques for cadence estimation.
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Acknowledgements
Project PID2019-106426RB-C32 funded by MCIN/AEI/10.13039/501100011033 and ERDF “A way to make Europe”. Project PDC2021-120997-C31 funded by MCIN/AEI/10.13039/501100011033 and European Union “NextGenerationEU”/PRTR. Project CIAICO/2021/037 funded by Generalitat Valenciana.
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Marin-Lora, C., Martin, M., Chover, M. (2023). A Face-Tracking Method for Estimating Cadence on Treadmills. In: Bravo, J., Ochoa, S., Favela, J. (eds) Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). UCAmI 2022. Lecture Notes in Networks and Systems, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-21333-5_94
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DOI: https://doi.org/10.1007/978-3-031-21333-5_94
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