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We present an extensive evaluation of 13 confidence metrics for stereo matching that compares the most widely used metrics as well as four novel techniques proposed here. We begin by categorizing the methods according to which aspects of stereo computation they take into account and, then, assess their strengths and weaknesses. The evaluation is conducted on indoor and outdoor datasets with ground...
We present a novel multi-baseline, multi-resolution stereo method, which varies the baseline and resolution proportionally to depth to obtain a reconstruction in which the depth error is constant. This is in contrast to traditional stereo, in which the error grows quadratically with depth, which means that the accuracy in the near range far exceeds that of the far range. This accuracy in the near...
The paper presents a system for automatic, geo-registered, real-time 3D reconstruction from video of urban scenes. The system collects video streams, as well as GPS and inertia measurements in order to place the reconstructed models in geo-registered coordinates. It is designed using current state of the art real-time modules for all processing steps. It employs commodity graphics hardware and standard...
We present a viewpoint-based approach for the quick fusion of multiple stereo depth maps. Our method selects depth estimates for each pixel that minimize violations of visibility constraints and thus remove errors and inconsistencies from the depth maps to produce a consistent surface. We advocate a two-stage process in which the first stage generates potentially noisy, overlapping depth maps from...
We formulate multi-view 3D shape reconstruction as the computation of a minimum cut on the dual graph of a semi- regular, multi-resolution, tetrahedral mesh. Our method does not assume that the surface lies within a finite band around the visual hull or any other base surface. Instead, it uses photo-consistency to guide the adaptive subdivision of a coarse mesh of the bounding volume. This generates...
We present an approach for 3D reconstruction from multiple video streams taken by static, synchronized and calibrated cameras that is capable of enforcing temporal consistency on the reconstruction of successive frames. Our goal is to improve the quality of the reconstruction by finding corresponding pixels in subsequent frames of the same camera using optical flow, and also to at least maintain the...
We present an evaluation methodology and data for large scale video-based 3D reconstruction. We evaluate the effects of several parameters and draw conclusions that can be useful for practical systems operating in uncontrolled environments. Unlike the benchmark datasets used for the binocular stereo and multi-view reconstruction evaluations, which were collected under well-controlled conditions, our...
Recent research has focused on systems for obtaining automatic 3D reconstructions of urban environments from video acquired at street level. These systems record enormous amounts of video; therefore a key component is a stereo matcher which can process this data at speeds comparable to the recording frame rate. Furthermore, urban environments are unique in that they exhibit mostly planar surfaces...
The paper introduces a data collection system and a processing pipeline for automatic geo-registered 3D reconstruction of urban scenes from video. The system collects multiple video streams, as well as GPS and INS measurements in order to place the reconstructed models in geo- registered coordinates. Besides high quality in terms of both geometry and appearance, we aim at real-time performance. Even...
We address multiple-view reconstruction under an optimization approach based on belief propagation. A novel formulation of belief propagation that operates in 3-D is proposed to facilitate a true multi-image processing scheme that takes visibility into account and thus is applicable to scenes that contain significant occlusions. Visibility is not approximated but is estimated and used in a modified...
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