The Eins3D project — Instantaneous UAV-Based 3D Mapping for Search and Rescue Applications

2019 ◽  
Author(s):  
Helge A. Lauterbach ◽  
C. Bertram Koch ◽  
Robin Hess ◽  
Daniel Eck ◽  
Klaus Schilling ◽  
...  
Keyword(s):  
Search And Rescue ◽  
3D Mapping

Robot-Assisted 3D Mapping of Search and Rescue Environments

2008 ◽  
Author(s):  
Zhe Zhang ◽  
Goldie Nejat
Keyword(s):  
Search And Rescue ◽  
3D Mapping ◽  
Urban Search And Rescue ◽  
Scale Invariant ◽  
Depth Images ◽  
Localization And Mapping ◽  
Landmark Identification ◽  
Robust Recognition ◽  
Sift Keypoints ◽  
2D Images

In this paper a unique landmark identification method is proposed for identifying large distinguishable landmarks for 3D Visual Simultaneous Localization and Mapping (SLAM) in unknown cluttered urban search and rescue (USAR) environments. The novelty of the method is the utilization of both 3D (i.e., depth images) and 2D images. By utilizing a Scale Invariant Feature Transform (SIFT) -based approach and incorporating 3D depth imagery, we can achieve more reliable and robust recognition and matching of landmarks from multiple images for 3D mapping of the environment. Preliminary experiments utilizing the proposed methodology verify: (i) its ability to identify clusters of SIFT keypoints in both 3D and 2D images for representation of potential landmarks in the scene, and (ii) the use of the identified landmarks in constructing a 3D map of unknown cluttered USAR environments.

Accurate 3D mapping and immersive visualization for Search and Rescue

2015 ◽  
Author(s):  
Pawel Musialik ◽  
Karol Majek ◽  
Piotr Majek ◽  
Michal Pelka ◽  
Janusz Bedkowski ◽  
...  
Keyword(s):  
Search And Rescue ◽  
3D Mapping ◽  
Immersive Visualization

3D Mapping of Verbal Memory in Clinical and Preclinical Alzheimer's Disease

2012 ◽  
Author(s):  
Jennifer A. Eastman ◽  
Kristy S. Hwang ◽  
Sona Babakchanian ◽  
Nicole Chow ◽  
Leslie Ramirez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Verbal Memory ◽  
3D Mapping ◽  
Preclinical Alzheimer’S Disease

ROC Analysis of Three Perfusion Display Options for ECG-gated Perfusion SPECT in Severe CAD

1999 ◽  
Vol 38 (06) ◽  
pp. 172-177
Author(s):  
H. Bailer ◽  
Marianne Gwechenberger ◽  
Martha Pruckmayer ◽  
A. Staudenherz ◽  
G. Kronik ◽  
...  
Keyword(s):  
Roc Analysis ◽  
Lateral Wall ◽  
Visual Assessment ◽  
3D Mapping ◽  
Operating Characteristics ◽  
Gated Perfusion Spect ◽  
Perfusion Spect ◽  
Coronary Stenoses ◽  
Definition Of ◽  
Valve Plane

Summary Aim: The simultaneous computation and display of wall motion and perfusion patterns in a single 3D ventricular model would considerably ease the assessment of ECG-gated Tc-99m-sestamibi SPECT, yet the effect on the accuracy of allocating regional perfusion has so far not been validated. Methods: 3D perfusion mapping (3D Perfusion/Motion Map Software) was compared to the visual assessment of ungated tomographic slices and polar perfusion mapping (Cedars-Sinai PTQ) by correlation analysis and receiver operating characteristics (ROC) analysis at different cut-off levels for coronary stenoses in 50 patients (11 single-, 22 two-, 16 three-vessel disease). Ungated SPECT data were obtained by adding the intervals prior to reconstruction and displaying conventional tomographic slices. All display options were visually assessed in 8 ventricular segments according to a 4-point scoring system and compared to the graded results of coronary angiography. Results: All three display options showed a comparable diagnostic performance for the detection of severe stenoses. The diagnostic gain for the detection of stenoses above 59% was highest for ungated tomographic slices, followed by ungated polar mapping and 3D mapping. Regional assessment revealed a limited performance of 3D mapping in the proximal anterior and distal lateral wall. Polar mapping showed a balanced regional performance. Conclusion: 3D Perfusion mapping provides comparable information to conventional display options with the highest diagnostic strength in severe stenoses. Further improvement of the algorithm is needed in the definition of the valve plane.

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