Benndorf, MaikRingsleben, FredericHaenselmann, ThomasYadav, BharatEibl, MaximilianGaedke, Martin2017-08-282017-08-282017978-3-88579-669-5Within this work-in-progress, we aim to automate the annotation of Sensor data for generating training data for Activity Recognition (AR) of multiple persons. Usually, the activities are executed and recorded from test persons under the supervision of an instructor, which may influence in many cases the natural behaviour of the test persons and the authenticity of the data. In this work, we suggest how this influence can be reduced and how the Sensor data can be annotated automatically by using video capturing, openpose for extracting human key points and a neuronal network to classify the activities. By automatically annotating the selected activities we show the feasibility of our approach.enActivity RecognitionAutomated AnnotationSensor dataOpenposeDeep Learning10.18420/in2017_2201617-5468