The 1st Challenge on Remote Physiological Signal Sensing (RePSS)
This work establishes a benchmark and validation platform for researchers in remote physiological sensing, facilitating progress in a field hindered by data availability, though it is incremental as it builds on existing methods without introducing new techniques.
The paper introduces the first challenge on Remote Physiological Signal Sensing (RePSS) to address the lack of public benchmarks for measuring physiological signals from videos, specifically focusing on average heart rate estimation from facial videos, and provides an overview including data, results, and top solutions.
Remote measurement of physiological signals from videos is an emerging topic. The topic draws great interests, but the lack of publicly available benchmark databases and a fair validation platform are hindering its further development. For this concern, we organize the first challenge on Remote Physiological Signal Sensing (RePSS), in which two databases of VIPL and OBF are provided as the benchmark for kin researchers to evaluate their approaches. The 1st challenge of RePSS focuses on measuring the average heart rate from facial videos, which is the basic problem of remote physiological measurement. This paper presents an overview of the challenge, including data, protocol, analysis of results and discussion. The top ranked solutions are highlighted to provide insights for researchers, and future directions are outlined for this topic and this challenge.