[ICIP 2021] Action Segmentation on Representations of Skeleton Sequences using Transformer Networks скачать в хорошем качестве

[ICIP 2021] Action Segmentation on Representations of Skeleton Sequences using Transformer Networks

Action Segmentation on Representations of Skeleton Sequences using Transformer Networks Simon Häring, Raphael Memmesheimer, Dietrich Paulus 2021 IEEE International Conference on Image Processing 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.