16,742 research outputs found
Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System
Az http://intechweb.org/ alatti "Books" fĂĽl alatt kell rákeresni a "Stereo Vision" cĂmre Ă©s az 1. fejezetre
Connectivity-Enforcing Hough Transform for the Robust Extraction of Line Segments
Global voting schemes based on the Hough transform (HT) have been widely used
to robustly detect lines in images. However, since the votes do not take line
connectivity into account, these methods do not deal well with cluttered
images. In opposition, the so-called local methods enforce connectivity but
lack robustness to deal with challenging situations that occur in many
realistic scenarios, e.g., when line segments cross or when long segments are
corrupted. In this paper, we address the critical limitations of the HT as a
line segment extractor by incorporating connectivity in the voting process.
This is done by only accounting for the contributions of edge points lying in
increasingly larger neighborhoods and whose position and directional content
agree with potential line segments. As a result, our method, which we call
STRAIGHT (Segment exTRAction by connectivity-enforcInG HT), extracts the
longest connected segments in each location of the image, thus also integrating
into the HT voting process the usually separate step of individual segment
extraction. The usage of the Hough space mapping and a corresponding
hierarchical implementation make our approach computationally feasible. We
present experiments that illustrate, with synthetic and real images, how
STRAIGHT succeeds in extracting complete segments in several situations where
current methods fail.Comment: Submitted for publicatio
Position and Volume Estimation of Atmospheric Nuclear Detonations from Video Reconstruction
Recent work in digitizing films of foundational atmospheric nuclear detonations from the 1950s provides an opportunity to perform deeper analysis on these historical tests. This work leverages multi-view geometry and computer vision techniques to provide an automated means to perform three-dimensional analysis of the blasts for several points in time. The accomplishment of this requires careful alignment of the films in time, detection of features in the images, matching of features, and multi-view reconstruction. Sub-explosion features can be detected with a 67% hit rate and 22% false alarm rate. Hotspot features can be detected with a 71.95% hit rate, 86.03% precision and a 0.015% false positive rate. Detected hotspots are matched across 57-109o viewpoints with 76.63% average correct matching by defining their location relative to the center of the explosion, rotating them to the alternative viewpoint, and matching them collectively. When 3D reconstruction is applied to the hotspot matching it completes an automated process that has been used to create 168 3D point clouds with 31.6 points per reconstruction with each point having an accuracy of 0.62 meters with 0.35, 0.24, and 0.34 meters of accuracy in the x-, y- and z-direction respectively. As a demonstration of using the point clouds for analysis, volumes are estimated and shown to be consistent with radius-based models and in some cases improve on the level of uncertainty in the yield calculation
InLoc: Indoor Visual Localization with Dense Matching and View Synthesis
We seek to predict the 6 degree-of-freedom (6DoF) pose of a query photograph
with respect to a large indoor 3D map. The contributions of this work are
three-fold. First, we develop a new large-scale visual localization method
targeted for indoor environments. The method proceeds along three steps: (i)
efficient retrieval of candidate poses that ensures scalability to large-scale
environments, (ii) pose estimation using dense matching rather than local
features to deal with textureless indoor scenes, and (iii) pose verification by
virtual view synthesis to cope with significant changes in viewpoint, scene
layout, and occluders. Second, we collect a new dataset with reference 6DoF
poses for large-scale indoor localization. Query photographs are captured by
mobile phones at a different time than the reference 3D map, thus presenting a
realistic indoor localization scenario. Third, we demonstrate that our method
significantly outperforms current state-of-the-art indoor localization
approaches on this new challenging data
- …