This paper presents a literature survey on existing disparity map algorithms. It focuses on
four main stages of processing as proposed by Scharstein and Szeliski in a taxonomy and …

A significant amount of research in the field of stereo vision has been published in the past
decade. Considerable progress has been made in improving accuracy of results as well as …

As an essential component for many autonomous driving and robotic activities such as ego-
motion estimation, obstacle avoidance and scene understanding, monocular depth …

Time-of-flight (TOF) cameras provide a depth value at each pixel, from which the 3D
structure of the scene can be estimated. This new type of active sensor makes it possible to …

We present an accurate stereo matching method using local expansion moves based on
graph cuts. This new move-making scheme is used to efficiently infer per-pixel 3D plane …

While machine learning has been instrumental to the ongoing progress in most areas of
computer vision, it has not been applied to the problem of stereo matching with similar …

We present an accurate and efficient stereo matching method using locally shared labels, a
new labeling scheme that enables spatial propagation in MRF inference using graph cuts …

Markov random fields (MRFs) are popular and generic probabilistic models of prior
knowledge in low-level vision. Yet their generative properties are rarely examined, while …

Binocular vision uses the parallax principle of the human eye to obtain 3D information of an
object, which is widely used as an important means of acquiring 3D information for 3D …

We present a deep architecture that estimates a stereo confidence, which is essential for
improving the accuracy of stereo matching algorithms. In contrast to existing methods based …