Particle Filtering for Tracking in 360 Degrees Videos Using Virtual PTZ Cameras

Abstract

360 degrees cameras are devices able to record spherical images of the environment. Such images can be used to generate views of the scene by projecting the spherical surface onto planes tangent to the sphere. Each of these views can be considered as the output of a virtual PTZ (vPTZ) camera with specific pan, tilt and zoom parameters. This paper proposes to formulate the visual tracking problem as the one of selecting, at each time, the vPTZ camera to foveate on the target from the unlimited set of simultaneously generated vPTZ camera views. Assuming that the selected vPTZ camera is a stochastic variable, the paper proposes to model the posterior distribution of the underlying stochastic process by means of a set of particles each representing a vPTZ camera view. Experiments on a publicly available dataset show that the proposed tracking strategy is viable and achieves state-of-the-art performance.