TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Ludl, Dennis
A1  - Gulde, Thomas
A1  - Curio, Cristóbal
T1  - Enhancing data-driven algorithms for human pose estimation and action recognition through simulation
JF  - IEEE transactions on intelligent transportation systems
N2  - Recognizing human actions, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Intelligent transport systems in particular face this challenge, as interactions with people are often required. The development and testing of technical perception solutions is done mostly on standard vision benchmark datasets for which manual labelling of sensory ground truth has been a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in these datasets, leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework, which offers to train and validate algorithms on various human-centred scenarios. We describe the usage of simulation data to train a state-of-the-art human pose estimation algorithm to recognize unusual human activities in urban areas. Since the recognition of human actions can be an important component of intelligent transport systems, we investigated how simulations can be applied for his purpose. Laboratory experiments show that we can train a recurrent neural network with only simulated data based on motion capture data and 3D avatars, which achieves an almost perfect performance in the classification of those human actions on real data.
KW  - simulation
KW  - machine learning
KW  - computer vision
KW  - recurrent neural networks
KW  - classification algorithms
KW  - autonomous vehicles
Y1  - 2020
SN  - 1524-9050
SS  - 1524-9050
U6  - https://doi.org/10.1109/TITS.2020.2988504
DO  - https://doi.org/10.1109/TITS.2020.2988504
VL  - 21
IS  - 9
SP  - 3990
EP  - 3999
S1  - 10
PB  - Inst. of Electrical and Electronics Engineers
CY  - New York
ER  -