Towards Practical, Best Practice Video Annotation to Support Human Activity Recognition.

ABSTRACT: Researchers need ground-truth activity annotations to train and evaluate wearable-sensor-based activity recognition models. Often-times, researchers establish ground truth by annotating the video recorded while someone engages in activity wearing sensors. The "gold-standard" video annotation practice requires two trained annotators independently annotating the same footage with a third domain expert resolving disagreements. Such annotation is laborious, and so widely-used datasets have often been annotated using only a single annotator per video. Because the research community is moving towards collecting data of more complex behaviors from free-living people 24/7 and annotating more granular, fleeting activities, the annotation task grows even more challenging; the single-annotator approa

SUBMITTER: Tran H 

PROVIDER: S-EPMC12799097 | biostudies-literature | 2026

REPOSITORIES: biostudies-literature