Abstract:
Spherical cameras are widely used due to their full 360^\circ fields of view. However, a common but severe problem is that anything carrying the camera is always includ...Show MoreMetadata
Abstract:
Spherical cameras are widely used due to their full 360^\circ fields of view. However, a common but severe problem is that anything carrying the camera is always included in the view, occluding visual information. In this letter, we propose a novel method to remove such occlusions in videos taken from a freely moving spherical camera. Our method can recover the occluded background accurately in distorted spherical videos by inpainting the color and motion information of pixels. The missing color and motion information inside the occluded region is iteratively recovered in a coarse-to-fine optimization. Spatial and temporal coherence of color and motion information is enforced, considering spherical image geometry. Initially, feature-point matching is used to remove the effect of camera rotation in order to deal with large pixel displacements. Following this, the iterative optimization process is bootstrapped using a reliable estimate of motion information obtained by interpolating it from surrounding regions. We demonstrate its effectiveness by successfully completing videos and recovering occluded regions recorded in various practical situations and by quantifying it against other state-of-the-art methods.
Published in: IEEE Robotics and Automation Letters ( Volume: 2, Issue: 4, October 2017)