Acoustic Doppler sonar for gait recogination
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
One-handed gesture recognition using ultrasonic Doppler sonar
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Human behavior understanding for inducing behavioral change: application perspectives
HBU'11 Proceedings of the Second international conference on Human Behavior Unterstanding
| Hi-index | 0.00 |
The spectrotemporal representation of an ultrasonar wave reflected by an object contains frequency shifts corresponding to the velocity of the object's moving parts, also known as the micro-Doppler signature. The present study describes how the micro-Doppler signature of human subjects, collected in two experiments, can be used to categorize the action performed by the subject. The proposed method segments the spectrogram into temporal events, learns prototypes and categorizes the events using a Nearest Neighbour approach. Results show an average accuracy above 95%, with some categories reaching 100%, and a strong robustness to variations in the model parameters. The low computational cost of the system, together with its high accuracy, even for short length inputs, make it appropriate for a real-time implementation with applications to intelligent surveillance, monitoring and related disciplines.