Abstract
Multi-view position recovery is common in the field of computer vision and applications range from commercial motion tracking to three-dimensional (3D) reconstruction of static environments. For these applications, one of two key assumptions is commonly assumed true: (1) camera information is synchronized across two or more offset cameras, (2) the environment being viewed is static. This work considers a simulation study of multi-view position approximations of a moving target in two dimensions (2D). The position is recovered using two or more 2D pinhole cameras. In this use case, images from cameras are asynchronous with respect to one another and extrinsic measurements. In simulations, the recovered target position varies widely from the true target position and uncertainty is injected using Monte Carlo methods to approximate a single probability distribution representing the target’s uncertain position in space. Results show a probability distribution that reasonably approximates the target’s true position in 2D space given sufficiently accurate extrinsic information.
