PT Journal
AU Ikechukwu Ofodile
   Ahmed Helmi
   Albert Clapes
   Egils Avots
   Kerttu Maria Peensoo
   Sandhra Mirella Valdma
   Andreas Valdmann
   Heli Valtna Lukner
   Sergey Omelkov
   Sergio Escalera
   Cagri Ozcinar
   Gholamreza Anbarjafari
TI Action recognition using single-pixel time-of-flight detection
SO Entropy
JI ENTROPY
PY 2019
BP 414
VL 21
IS 4
DI 10.3390/e21040414
DE single pixel single photon image acquisition; time-of-flight; action recognition
AB Action recognition is a challenging task that plays an important role in many robotic systems, which highly depend on visual input feeds. However, due to privacy concerns, it is important to find a method which can recognise actions without using visual feed. In this paper, we propose a concept for detecting actions while preserving the test subject’s privacy. Our proposed method relies only on recording the temporal evolution of light pulses scattered back from the scene.Such data trace to record one action contains a sequence of one-dimensional arrays of voltage values acquired by a single-pixel detector at 1 GHz repetition rate. Information about both the distance to the object and its shape are embedded in the traces. We apply machine learning in the form of recurrent neural networks for data analysis and demonstrate successful action recognition. The experimental results show that our proposed method could achieve on average 96.47% accuracy on the actions walking forward, walking backwards, sitting down, standing up and waving hand, using recurrentneural network.
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