Exiting deep-learning based dense stereo matching methods often rely on ground-truth disparity maps as the training signals, which are however not always available in many situations. In this paper, we design a simple convolutional neural network architecture that is able to learn to compute dense disparity maps directly from the stereo inputs. Training is performed in an end-to-end fashion wit...

Stereopsis is the computation of depth information from views acquired simultaneously from different points in space. For many years, stereopsis was thought to be confined to primates and other mammals with front-facing eyes. However, stereopsis has now been demonstrated in many other animals, including lateral-eyed prey mammals, birds, amphibians and invertebrates. The diversity of animals kno...

The High Resolution Stereo Camera – Airborne (HRSC-A), a multispectral multi-line/multi-stereo scanner system, developed at the German Aerospace Center DLR, has been successfully applied in many flight campaigns during the past two years. Together with a comprehensive software package for automated photogrammetric processing it has been used for many investigations in different disciplines. Thi...

In our related work, we proposed Auto Focus for stereo camera. Instead of moving optical axis Cognitive Stereo Auto Focus shifts one side image to the o side for setting focus. In the shifting process, be set on the proper place not to cause any side by visual fatigue to user. To perform low visual fatigue focusing, Cognitive Stereo Auto Focus analyzes the input scene and find how many objects ...

In this paper, we formulate the stereo matching problem as a Markov network and solve it using Bayesian belief propagation. The stereo Markov network consists of three coupled Markov random fields that model the following: a smooth field for depth/disparity, a line process for depth discontinuity, and a binary process for occlusion. After eliminating the line process and the binary process by i...

This report provides a brief and informal introduction into stereo and motion analysis for driver assistance. Stereo and motion analysis play a central role in computer vision [10]. Many algorithms in this field have been proposed and carefully studied; see, for example, [2, 14] and the website vision.middlebury.edu for stereo and optic flow algorithms. In short, a stereo pair of images allows ...

Estimating its ego-motion is one of the most important capabilities for an autonomous mobile platform. Without reliable ego-motion estimation no long-term navigation is possible. Besides odometry, inertial sensors, DGPS, laser range finders and so on, vision based algorithms can contribute a lot of information. Stereo odometry is a vision based motion estimation algorithm that estimates the ego...

Full panoramic images, covering 360 degrees, can be created either by using panoramic cameras or by mosaicing together many regular images. Creating panoramic views in stereo, where one panorama is generated for the left eye, and another panorama is generated for the right eye is more problematic. Earlier attempts to mosaic images from a rotating pair of stereo cameras faced severe problems of ...

Estimating its ego-motion is one of the most important capabilities for an autonomous mobile platform. Without reliable ego-motion estimation no long-term navigation is possible. Besides odometry, inertial sensors, DGPS, laser range finders and so on, vision based algorithms can contribute a lot of information. Stereo odometry is a vision based motion estimation algorithm that estimates the ego...

In this paper, CMU video-rate stereo machine based on multi-baseline method is introduced. It is a dedicated hardware for very fast range measurement. A calibration method suitable for multi-baseline stereo is also shown. Finally the performance is demonstrated in an indoor scene. Direct motivation of the development of stereo machine is to use it as a range sensor in autonomous navigation vehi...