Paper ID | IFS-2.8 | ||
Paper Title | ACTION SEGMENTATION ON REPRESENTATIONS OF SKELETON SEQUENCES USING TRANSFORMER NETWORKS | ||
Authors | Simon Häring, Raphael Memmesheimer, Dietrich Paulus, University of Koblenz-Landau, Germany | ||
Session | IFS-2: Information Forensics and Security | ||
Location | Area K | ||
Session Time: | Monday, 20 September, 15:30 - 17:00 | ||
Presentation Time: | Monday, 20 September, 15:30 - 17:00 | ||
Presentation | Poster | ||
Topic | Information Forensics and Security: Surveillance | ||
IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
Abstract | We propose an approach for action segmentation by representing motions as images. A transformer object detection network is used to segment the sequences from the representation images. We examine different encoding approaches, normalization strategies and skeleton joint orders in an extensive experiment study. Our approach is evaluated on skeleton sequences from the PKU-MMD dataset. We successfully apply transformer networks for action segmentation on skeleton sequences. Our proposed approach achieves high class accuracies while start and end-time estimation of the action segments are subject to further improvement. |