Improving state estimation through projection post-processing for activity recognition with application to football. (arXiv:2102.03310v3 [cs.CV] UPDATED)

The past decade has seen an increased interest in human activity recognition
based on sensor data. Most often, the sensor data come unannotated, creating
the need for fast labelling methods. For assessing the quality of the
labelling, an appropriate performance measure has to be chosen. Our main
contribution is a novel post-processing method for activity recognition. It
improves the accuracy of the classification methods by correcting for
unrealistic short activities in the estimate. We also propose a new performance
measure, …

application arxiv football processing projection state