A dataset of annotated omnidirectional videos for distancing applications

Omnidirectional (or 360◦ ) cameras are acquisition devices that, in the next few years, could have a big impact on video surveillance applications, research, and industry, as they can record a spherical view of a whole environment from every perspective. This paper presents two new contributions to the research community: the CVIP360 dataset, an annotated dataset of 360◦ videos for distancing applications, and a new method to estimate the distances of objects in a scene from a single 360◦ image. The CVIP360 dataset includes 16 videos acquired outdoors and indoors, annotated by adding information about the pedestrians in the scene (bounding boxes) and the distances to the camera of some points in the 3D world by using markers at fixed and known intervals. The proposed distance estimation algorithm is based on geometry facts regarding the acquisition process of the omnidirectional device, and is uncalibrated in practice: the only required parameter is the camera height. The proposed algorithm was tested on the CVIP360 dataset, and empirical results demonstrate that the estimation error is negligible for distancing applications

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

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