Light-field imaging is based on images taken on a regular grid. Thus, high-quality 3D reconstructions are obtainable by analyzing orientations in epipolar plane images (EPIs). Unfortunately, such data only allows to evaluate one side of the object. Moreover, a constant intensity along each orientation is mandatory for most of the approaches. This paper presents a novel method which allows to reconstruct depth information from data acquired with a circular camera motion, termed circular light fields. With this approach it is possible to determine the full 360° view of target objects. Additionally, circular light fields allow retrieving depth from datasets acquired with telecentric lenses, which is not possible with linear light fields. The proposed method finds trajectories of 3D points in the EPIs by means of a modified Hough transform. For this purpose, binary EPI-edge images are used, which not only allow to obtain reliable depth information, but also overcome the limitation of constant intensity along trajectories. Experimental results on synthetic and real datasets demonstrate the quality of the proposed algorithm.

Among all the techniques for 3D acquisition, stereo vision systems are the most common. More recently, Time-of-Flight (ToF) range cameras have been introduced. They allow real-time depth estimation in conditions where stereo does not work well. Unfortunately, ToF sensors still have a limited resolution (e.g., 200 × 200 pixels). The goal of this paper is to combine the information from the ToF with one or two standard cameras, in order to obtain a highresolution depth image. To this end, we propose a new bilateral filter for depth maps up-sampling, which exploits the additional information provided by a high-resolution color image. Moreover, we present an entire framework for the super-resolution of a real ToF depth map with a single camera color image. The algorithm allows to enhance the resolution of the ToF camera depth image up to 1920 × 1080 pixels.