Classification in C-band of Doppler signatures of human activities in indoor environment
Résumé
This paper explains CentraleSupélec team's approach for the challenge of human activity classification with radar [1]. Our methodology is based on a convolutional network classifier processing the range-time and spectrogram representations. The preprocessing and the neural network architecture presented in this paper allowed us to reach 99% accuracy on challenge's test data of the challenge. A more advanced preprocessing using wavelets is also briefly discussed. Index Terms-Human activity classification, deep convolutional neural networks, spectrogram, Doppler-range diagram, rangetime diagram.