Multiple temporal texture detection using feature space mapping

Characterization of visual processes consisting of multiple temporal textures is of vital importance to computer vision research, with a diverse set of applications in the field of robot navigation, remote monitoring (for the prevention of natural disasters), traffic monitoring, and homeland security applications etc. In the current literature of temporal textures, however studies are mostly limited to characterization of single temporal textures. In this paper we aim to address the problem of detecting the presence of multiple temporal textures in an image sequence for real time situations like bushfire monitoring by establishing a correspondence between feature space of temporal textures and that of their mixture in an image sequence. Accuracy of our proposed technique is both analytically and empirically established with detection experiments yielding 92.5% average accurate detection rate on a diverse set of temporal texturemixtures.