scholarly journals Projective 3D-reconstruction of Uncalibrated Endoscopic Images

10.14311/1225 ◽  
2010 ◽  
Vol 50 (4) ◽  
Author(s):  
P. Faltin ◽  
A. Behrens
Keyword(s):  
3D Reconstruction ◽  
Bladder Wall ◽  
Urinary Bladder Cancer ◽  
Image Sequences ◽  
Endoscopic Image ◽  
Medical Diagnostic ◽  
3D Scene ◽  
3D Information ◽  
Scene Content ◽  
Ransac Algorithm

The most common medical diagnostic method for urinary bladder cancer is cystoscopy. This inspection of the bladder is performed by a rigid endoscope, which is usually guided close to the bladder wall. This causes a very limited field of view; difficulty of navigation is aggravated by the usage of angled endoscopes. These factors cause difficulties in orientation and visual control. To overcome this problem, the paper presents a method for extracting 3D information from uncalibrated endoscopic image sequences and for reconstructing the scene content. The method uses the SURF-algorithm to extract features from the images and relates the images by advanced matching. To stabilize the matching, the epipolar geometry is extracted for each image pair using a modified RANSAC-algorithm. Afterwards these matched point pairs are used to generate point triplets over three images and to describe the trifocal geometry. The 3D scene points are determined by applying triangulation to the matched image points. Thus, these points are used to generate a projective 3D reconstruction of the scene, and provide the first step for further metric reconstructions.

scholarly journals Partial 3D-reconstruction of the colon from monoscopic colonoscopy videos using shape-from-motion and deep learning

2021 ◽  
Vol 7 (2) ◽  
pp. 335-338
Author(s):  
Sina Walluscheck ◽  
Thomas Wittenberg ◽  
Volker Bruns ◽  
Thomas Eixelberger ◽  
Ralf Hackner
Keyword(s):  
3D Reconstruction ◽  
Point Clouds ◽  
Image Sequences ◽  
Video Streams ◽  
Deep Convolutional Neural Networks ◽  
Depth Maps ◽  
Endoscopic Video ◽  
Successive Image ◽  
3D Information ◽  
Standard Colonoscopy

Abstract For the image-based documentation of a colonoscopy procedure, a 3D-reconstuction of the hollow colon structure from endoscopic video streams is desirable. To obtain this reconstruction, 3D information about the colon has to be extracted from monocular colonoscopy image sequences. This information can be provided by estimating depth through shape-from-motion approaches, using the image information from two successive image frames and the exact knowledge of their disparity. Nevertheless, during a standard colonoscopy the spatial offset between successive frames is continuously changing. Thus, in this work deep convolutional neural networks (DCNNs) are applied in order to obtain piecewise depth maps and point clouds of the colon. These pieces can then be fused for a partial 3D reconstruction.

An Approach to Automatic Great-Scene 3D Reconstruction Based on UAV Sequence Images

2012 ◽  
Vol 229-231 ◽  
pp. 2294-2297
Author(s):  
Zi Ming Xiong ◽  
Gang Wan
Keyword(s):  
3D Reconstruction ◽  
Feature Vector ◽  
Image Sequences ◽  
Bundle Adjustment ◽  
Image Feature ◽  
Perspective Projection ◽  
Projection Model ◽  
New Thinking ◽  
Optimal Triangulation ◽  
3D Scene

In this paper, we propose an approach to automatic great-scene 3D reconstruction based on UAV sequence images. In this method, Harris feature point and SIFT feature vector is used to distill image feature, achieving images match; quasi-perspective projection model and factorization is employed to calibrate the uncalibrated image sequences automatically; Efficient suboptimal solutions to the optimal triangulation is plied to obtain the coordinate of 3D points; quasi-dense diffusing algorithm is bestowed to make 3D point denseness; the algorithm of bundle adjustment is taken to improve the precision of 3D points; the approach of Possion surface reconstruction is used to make 3D points gridded. This paper introduces the theory and technology of computer vision into great-scene 3D reconstruction, provides a new way for the construction of 3D scene, and provides a new thinking for the appliance of UAV sequence images.

3D Reconstruction Using Multiple View Stereo and a Brief Introduction to Kinect

2014 ◽  
pp. 15-37
Author(s):  
Brojeshwar Bhowmick
Keyword(s):  
3D Reconstruction ◽  
Projective Geometry ◽  
Point Cloud ◽  
Microsoft Kinect ◽  
Sparse Reconstruction ◽  
Basic Properties ◽  
Multiple View ◽  
The Subject ◽  
Dense Reconstruction ◽  
3D Information

This chapter deals with the methodology of 3D reconstruction, both sparse and dense. The basic properties of the projective geometry and the camera models are introduced to understand the preliminaries about the subject. A more detail can be found in the book (Hartley & Zisserman, 2000). The sparse reconstruction deals with reconstructing 3D points for few image points. There are gaps in the reconstructed 3D points. Dense reconstruction tries to fill up gaps and make the density of the reconstruction higher. Estimation of correspondences is an integral part of multiview reconstruction and the author will discuss the point correspondences among images here. Finally the author will introduce the Microsoft Kinect, a divice which directly capture 3D information in realtime, and will show how to enhance the Kinect point cloud using vision framework.

scholarly journals The Use of Gigapixel Photogrammetry for the Understanding of Landslide Processes in Alpine Terrain

Geosciences ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 99 ◽  
Author(s):  
Saverio Romeo ◽  
Lucio Di Matteo ◽  
Daniel Kieffer ◽  
Grazia Tosi ◽  
Aurelio Stoppini ◽  
...  
Keyword(s):  
3D Model ◽  
Low Cost ◽  
Three Dimensional ◽  
Image Sequences ◽  
Synthetic Aperture ◽  
Synthetic Aperture Radar Interferometry ◽  
Experimental Application ◽  
Single Lens ◽  
Landslide Processes ◽  
3D Information

The work in this paper illustrates an experimental application for geosciences by coupling new and low cost photogrammetric techniques: Gigapixel and Structure-from-Motion (SfM). Gigapixel photography is a digital image composed of billions of pixels (≥1000 megapixels) obtained from a conventional Digital single-lens reflex camera (DSLR), whereas the SfM technique obtains three-dimensional (3D) information from two-dimensional (2D) image sequences. The field test was carried out at the Ingelsberg slope (Bad Hofgastein, Austria), which hosts one of the most dangerous landslides in the Salzburg Land. The stereographic analysis carried out on the preliminary 3D model, integrated with Ground Based Synthetic Aperture Radar Interferometry (GBInSAR) data, allowed us to obtain the main fractures and discontinuities of the unstable rock mass.

A Novel Method for Automated Acquisition of Tilt Series for Electron Tomography Based on Pre-Calibration of the Specimen Stage

2000 ◽  
Vol 6 (S2) ◽  
pp. 1148-1149
Author(s):  
U. Ziese ◽  
A.H. Janssen ◽  
T.P. van der Krift ◽  
A.G. van Balen ◽  
W.J. de Ruijter ◽  
...  
Keyword(s):  
High Resolution ◽  
3D Reconstruction ◽  
Cell Biology ◽  
Electron Tomography ◽  
Three Dimensional ◽  
Imaging Method ◽  
3D Images ◽  
Tilt Series ◽  
3D Information ◽  
Structural Arrangements

Electron tomography is a three-dimensional (3D) imaging method with transmission electron microscopy (TEM) that provides high-resolution 3D images of structural arrangements. Conventional TEM images are in first approximation mere 2D-projections of a 3D sample under investigation. With electron tomographya series of images is acquired of a sample that is tilted over a large angular range (±70°) with small angular tilt increments (so called tilt-series). For the subsequent 3D-reconstruction, the images of the tilt series are aligned relative to each other and the 3D-reconstruction is computed. Electron tomography is the only technique that can provide true 3D information with nm-scale resolution of individual and unique samples. For (cell) biology and material science applications the availability of high-resolution 3D images of structural arrangements within individual samples provides unique architectural information that cannot be obtained otherwise. Routine application of electron tomography will comprise a major revolutionary step forward in the characterization of complex materials and cellular arrangements.

Volume Measurement Method for Irregular Objects Based on Shape from Shading

2014 ◽  
Vol 494-495 ◽  
pp. 789-792
Author(s):  
Hong She Dang ◽  
Chu Jia Guo
Keyword(s):  
3D Reconstruction ◽  
Measurement Method ◽  
Convex Surface ◽  
Shape From Shading ◽  
Volume Measurement ◽  
Intensity Level ◽  
Reconstruction Method ◽  
Regular Shape ◽  
Image Acquisition System ◽  
3D Information

In this paper, we propose a volume measurement method for irregular objects. And three cameras were used in the image acquisition system. In order to reduce the intensity level and be more coincident with the 3D reconstruction method, a method called Histogram Acceleration has been used. Instead of using the regular shape from shading method, the relation between intensity and the missed 3D information was found. This method is valid within a certain error range. Its showed by experiment that this method has a good performance when dealing with objects with a smooth and convex surface.

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