ActivityNet

Purpose

Various approaches for movement analysis have been proposed in literature. Up to date, it is not clear which solution is outperforming the others. The provision of benchmark datasets is mandatory for research groups. This could enhance and speed up the process of getting the best performing and most appropriate algorithm for movement analysis. Below, you can find currently available datasets. Please press the link for a more detailed description. If you are interested in sharing your database, please feel free to contact info(at)activitynet.org for more information.

Datasets

• DaLiAc – Daily Life Activities
• BaSA – Basic Step Activities
• EnEx – Energy Expenditure
• Digital Biobank
• GaitPhase Database
• Sensor-based Gait Analysis Validation Data (Kluge et al. 2017)
• Smart Annotation Cyclic Activities Dataset (Martindale et al. 2017)
• Wearable multi-sensor gait-based daily activity data (Martindale et al ARDUOUS 2018)
• Benchmark cyclic activity recognition database using wearables

Imprint

Friedrich-Alexander-University Erlangen-Nuremberg
Machine Learning and Data Analytics Lab
Carl-Thiersch-Straße 2b, 91052 Erlangen, Germany
Phone (Secretary): +49 9131 85 28990
E-Mail: info(at)activitynet.org
Managing director: Bjoern M. Eskofier