Towards systematic benchmarking of activity recognition algorithms


Sztyler, Timo ; Meilicke, Christian ; Stuckenschmidt, Heiner



DOI: https://doi.org/10.1109/PERCOMW.2018.8480409
URL: https://ieeexplore.ieee.org/document/8480409
Additional URL: https://sensor.informatik.uni-mannheim.de/publicat...
Document Type: Conference or workshop publication
Year of publication: 2018
Book title: 2018 IEEE International Conference on Pervasive Computing and Communications workshops (PerCom workshops) : 2018 IEEE International Conference on Pervasive Computing and Communications workshops (PerCom workshops), 19-23 March 2018 in Athens, Greece
Page range: 15-20
Conference title: CoMoRea '18: 14th Workshop on Context and Activity Modeling and Recognition : affiliated to IEEE PerCom 2018
Location of the conference venue: Athens, Greece
Date of the conference: 19.-23.03.2018
Place of publication: Piscataway, NJ
Publishing house: IEEE Computer Society
ISBN: 978-1-5386-3227-7 , 978-1-5386-3226-0 , 978-1-5386-3228-4
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: In this paper we propose a benchmarking framework for evaluating activity recognition methods. We use an ontology for describing activity recognition datasets on the meta-level and propose a fine-grained annotation scheme for activity recognition datasets. Given a method that implements a defined interface, an evaluation client can be used to automatically run experiments on annotated datasets. Our framework helps to find relevant datasets and makes results reproducible by fixing concrete experimental settings. We show how to use the framework and report about a preliminary evaluation experiment.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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