Dynamic fire modeling in Three-dimensional space

This work presents a new framework for three-dimensional reconstruction of dynamic fire fronts found in outdoor unstructured scenes. The proposed approach addresses the problem of segmenting fire front regions using color attributes and clustering techniques in order to extract salient points from stereo images. These points are then used to reconstruct their 3D position in the scene. A matching strategy is proposed to deal with mismatches due to occlusions and missing data. The proposed framework was successfully used to build 3D data part of dynamic fire fronts. This 3D information was used efficiently to estimate the approximate position of the fire front and its heading direction. The obtained results are promising and show the possibility of tracking dynamic objects with changing shapes like fire fronts in a three-dimensional space.