Fire and smoke dynamic textures characterization by applying periodicity index based on motion features

Abstract

Dynamic texture has been described as images sequence that demonstrates continuous movement of pixels intensity change patterns in time. We consider the motion features of smoke and fire dynamic textures, which are important for fire calamity surveillance system to analyze the fire situation. We propose a method to understand the motion of intensity change. The objective is not only for classification purpose but also to characterize the motion pattern of fire and smoke dynamic texture. The radius of vector usually describes how fast the intensity change. The motion coherence index has been developed to assess the motion coherency between observed vector and its neighborhoods. We implement strategic motion coherence analysis to determine the motion coherence index of motion vector field in each video frame. In practical, both covariance stationarity of average radius and motion coherence index are efficiently used to investigate fire and smoke characteristics by applying periodicity index for analysis.