@misc{GedatFechnerFiebelkornetal.2018, author = {Gedat, Egbert and Fechner, Pascal and Fiebelkorn, Richard and Vandenhouten, Jan and Vandenhouten, Ralf}, title = {Image recognition of multi-perspective data for intelligent analysis of gestures and actions}, series = {Wissenschaftliche Beitr{\"a}ge 2018}, volume = {22}, journal = {Wissenschaftliche Beitr{\"a}ge 2018}, issn = {0949-8214}, doi = {10.15771/0949-8214_2018_3}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus4-10230}, pages = {25 -- 30}, year = {2018}, abstract = {The BERMUDA project started in January 2015 and was successfully completed after less than three years in August 2017. A technical set-up and an image processing and analysis software were developed to record and evaluate multi-perspective videos. Based on two cameras, positioned relatively far from one another with tilted axes, synchronized videos were recorded in the laboratory and in real life. The evaluation comprised the background elimination, the body part classification, the clustering, the assignment to persons and eventually the reconstruction of the skeletons. Based on the skeletons, machine learning techniques were developed to recognize the poses of the persons and next for the actions performed. It was, for example, possible to detect the action of a punch, which is relevant in security issues, with a precision of 51.3 \% and a recall of 60.6 \%.}, language = {en} }