Visual-Thermal Fusion-Based Object Tracking via a Granular Computing Backed Particle Filtering
Satbir Singh, Arun Khosla, Rajiv Kapoor · IETE Journal of Research · 2022
The proposed research aims to enhance the capabilities of information fusion-based object tracking using thermal and visible imaging. An essential motivation behind this technique is to carve out a framework that may utilize many attributes from several sensors. The built-in particle filter is adapted with the granular computing concept for weighing the particles. Furthermore, the algorithm is extended to obtain source-level fusion after the attribute weight adaptation. After comparing with the state-of-the-art methods, the results obtained suggest that it outperforms the compared trackers from the literature.