This short paper proposes a method for computing depth maps from multiple satellite cameras and fusing them to an enhanced one for the principal camera of a movie production. Additional precision is gathered from optionally adding a Time-of-Flight camera. The proposed algorithm is a generalization of the PatchMatch Stereo algorithm [1]. It calculates multiple stereo depth maps without the need ...

In this paper we consider the problem of single monocular image depth estimation. It is a challenging problem due to its ill-posedness nature and has found wide application in industry. Previous efforts belongs roughly to two families: learning-based method and interactive method. Learning-based method, in which deep convolutional neural network (CNN) is widely used, can achieve good result. Bu...

View-based 3D video streaming requires the compression and transmission of depth maps along with the video sequence. The requirements for representing these depth maps include moderately high compression, preservation of depth discontinuities, low complexity decoding, and to be in a form that is suitable for real-time rendering using graphics cards. This motivates a meshbased representation for...

In this paper, we present a novel real-time algorithm to refine depth maps generated by low-cost commercial depth sensors like the Microsoft Kinect. The Kinect sensor falls under the category of RGB-D sensors that can generate a high resolution depth map and color image of a scene. They are relatively inexpensive and are commercially available off-the-shelf. However, owing to their low complexi...

We revisit the problem of estimating depth of a scene from its single RGB image. Despite the recent success of deep learning based methods, we show that there is still room for improvement in two aspects by training a deep network consisting of two sub-networks; a base network for providing an initial depth estimate, and a refinement network for refining it. First, spatial resolution of the est...

The recent successful commercialization of depth sensors has made it possible to effectively capture depth images in real time, and thus creates a new modality for many computer vision tasks including hand gesture recognition and activity analysis. Most existing depth descriptors simply encode depth information as intensities while ignoring the richer 3D shape information. In this paper, we pro...

Sensing three-dimensional shape is a central problem in the development of robot systems for autonomous navigation and manipulation. Stereo vision is an attractive approach to this problem in several applications; however, stereo algorithms still lack reliability and generality. We address these problems by modelling the stereo depth map as a discrete random field, by formulating the matching p...

Chao-Chung Cheng (SID Student Member) Chung-Te Li Liang-Gee Chen Abstract — With the maturation of three-dimensional (3-D) technologies, display systems can provide higher visual quality to enrich the viewer experience. However, the depth information required for 3-D displays is not available in conventional 2-D recorded contents. Therefore, the conversion of existing 2-D video to 3-D video bec...