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2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2017)
Lecce, Italy
Aug. 29, 2017 to Sept. 1, 2017
ISBN: 978-1-5386-2940-6
pp: 1-6
A. Belmonte-Hernandez , Visual Telecommunications Applications Group, Universidad Politécnica de Madrid, Spain
V. Solachidis , Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece
T. Theodoridis , Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece
G. Hernandez-Penaloza , Visual Telecommunications Applications Group, Universidad Politécnica de Madrid, Spain
G. Conti , Visual Telecommunications Applications Group, Universidad Politécnica de Madrid, Spain
N. Vretos , Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece
F. Alvarez , Visual Telecommunications Applications Group, Universidad Politécnica de Madrid, Spain
P. Daras , Centre for Research and Technology Hellas, Information Technologies Institute, Thessaloniki, Greece
ABSTRACT
In this paper, a novel multi-modal method for person identification in indoor environments is presented. This approach relies on matching the skeletons detected by a Kinect v2 device with wearable devices equipped with inertial sensors. Movement features such as yaw and pitch changes are employed to associate a particular Kinect skeleton to a person using the wearable. The entire process of sensor calibration, feature extraction, synchronization and matching is detailed in this work. Six detection scenarios were defined to assess the proposed method. Experimental results have shown a high accuracy in the association process.
INDEX TERMS
Feature extraction, Wrist, Skeleton, Acceleration, Calibration, Visualization, Tools
CITATION

A. Belmonte-Hernandez et al., "Person tracking association using multi-modal systems," 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Lecce, Italy, 2017, pp. 1-6.
doi:10.1109/AVSS.2017.8078529
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