In this paper the application, performance and results of a fully discrete micro-Doppler feature classication processing chain utilising Krawtchouk moment invariants are presented. The approach demonstrates to be capable of running on low power hardware such as the Raspberry Pi 2. The effectiveness of the proposed approach is veried through the use of real K-band data in real-time.
|Number of pages||6|
|Publication status||Published - 14 Dec 2016|
|Event||11th IMA International Conference on Mathematics in Signal Processing - IET Austin Court, Birmingham, United Kingdom|
Duration: 12 Dec 2016 → 14 Dec 2016
|Conference||11th IMA International Conference on Mathematics in Signal Processing|
|Period||12/12/16 → 14/12/16|
- krawtchouk moments
- Raspberry Pi
- autonomous systems
Aßmann, A., Izzo, A., & Clemente, C. (2016). Efficient micro-doppler based pedestrian activity classification for ADAS systems using Krawtchouk moments. Poster session presented at 11th IMA International Conference on Mathematics in Signal Processing , Birmingham, United Kingdom.