Motion Based Particle Filter for Human Tracking with Thermal Imaging

Motion Tracking has been applied in many recent applications like surveillance, advance driver assistance system (ADAS), non-cooperative biometrics, virtual reality, etc. Current research in this field includes making tracking system more robust and reliable. Imaging modality to be used in motion tracking also includes thermal imaging (FIR) in addition to the visible imaging. We propose here a motion tracking algorithm using only thermal imaging. The particle filter uses motion based features pre-processed with Wigner distribution. The comparison between the performance measure obtained for thermal and visible imaging is also presented. The results obtained with the proposed system show the robustness of the algorithm. Additionally, the algorithm has less computational complexity as calculation of motion based features requires fewer computations.