A Photon-Mapping Informed Chan-Vese Segmentation Algorithm to Enable Multispectral Sensing and Path-Planning in 3D Virtual Environments

Understanding how to provide better surveillance in areas not viewable by visible light can arrive by modeling a virtual environment illuminated by photons in the non-visible spectrum and providing the mobile sensing platforms (MSPs) populating these environments with the tools to maximize their sensing capabilities. In order to enhance MSP sensing ability as well as enable MSP route path-planning, we propose a 3D segmentation algorithm based upon the Chan-Vese method to create a connected 3D mesh within the MSPs´ photon-mapping-illuminated virtual environment. The resulting segmentation mesh´s vertices contain more photons to be sensed by an MSP traversing the mesh than could have been sensed if the MSP had traveled elsewhere. The connectedness of the segmentation mesh gives the MSP uninterrupted travel through these highly-illuminated areas and allows for a variety of mission-planning scenarios. The initialization problem inherent to the Chan-Vese segmentation algorithm is overcome in a novel way by using output from an algorithm solving the art gallery problem to produce an initial segmentation curve comprised of vertices which are highly distinguished from their neighbors. The results of our segmentation algorithm enables an MSP to focus its attention on areas in the 3D environment that maximize the (non-)visible spectrum photons obtainable by their sensors or conversely explore areas have not been well-illuminated.