P‐49: Student Poster: Efficient Direct‐Block‐Address Encoding for Single‐Shot‐Based 3D Reconstruction

2021 ◽  
Vol 52 (1) ◽  
pp. 1250-1253
Author(s):  
Sina Farsangi ◽  
Mohamed A. Naiel ◽  
Mark Lamm ◽  
Paul Fieguth
Keyword(s):  
3D Reconstruction ◽  
Single Shot

scholarly journals 3D Reconstruction with Single-Shot Structured Light RGB Line Pattern

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4819
Author(s):  
Yikang Li ◽  
Zhenzhou Wang
Keyword(s):  
3D Reconstruction ◽  
Moving Objects ◽  
Structured Light ◽  
Color Space ◽  
Reconstruction Technique ◽  
Single Shot ◽  
Line Pattern ◽  
Hsv Color Space ◽  
Phase Map ◽  
Line Segmentation

Single-shot 3D reconstruction technique is very important for measuring moving and deforming objects. After many decades of study, a great number of interesting single-shot techniques have been proposed, yet the problem remains open. In this paper, a new approach is proposed to reconstruct deforming and moving objects with the structured light RGB line pattern. The structured light RGB line pattern is coded using parallel red, green, and blue lines with equal intervals to facilitate line segmentation and line indexing. A slope difference distribution (SDD)-based image segmentation method is proposed to segment the lines robustly in the HSV color space. A method of exclusion is proposed to index the red lines, the green lines, and the blue lines respectively and robustly. The indexed lines in different colors are fused to obtain a phase map for 3D depth calculation. The quantitative accuracies of measuring a calibration grid and a ball achieved by the proposed approach are 0.46 and 0.24 mm, respectively, which are significantly lower than those achieved by the compared state-of-the-art single-shot techniques.

scholarly journals The Lightfield Microscope Eyepiece

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6619
Author(s):  
Nicolò Incardona ◽  
Ángel Tolosa ◽  
Gabriele Scrofani ◽  
Manuel Martinez-Corral ◽  
Genaro Saavedra
Keyword(s):  
3D Reconstruction ◽  
Time Resolution ◽  
Optical Design ◽  
Three Dimensional ◽  
Fourier Integral ◽  
Single Shot ◽  
Proof Of Concept ◽  
Novel Device ◽  
Translation Stage ◽  
Commercial Device

Lightfield microscopy has raised growing interest in the last few years. Its ability to get three-dimensional information about the sample in a single shot makes it suitable for many applications in which time resolution is fundamental. In this paper we present a novel device, which is capable of converting any conventional microscope into a lightfield microscope. Based on the Fourier integral microscope concept, we designed the lightfield microscope eyepiece. This is coupled to the eyepiece port, to let the user exploit all the host microscope’s components (objective turret, illumination systems, translation stage, etc.) and get a 3D reconstruction of the sample. After the optical design, a proof-of-concept device was built with off-the-shelf optomechanical components. Here, its optical performances are demonstrated, which show good matching with the theoretical ones. Then, the pictures of different samples taken with the lightfield eyepiece are shown, along with the corresponding reconstructions. We demonstrated the functioning of the lightfield eyepiece and lay the foundation for the development of a commercial device that works with any microscope.

scholarly journals Rectification Based Single-Shot Structured Light for Accurate and Dense 3D Reconstruction

2021 ◽  
Vol 6 (1) ◽  
pp. 1-3
Author(s):  
Sina Farsangi ◽  
Mohamed A. Naiel ◽  
Mark Lamm ◽  
Paul Fieguth
Keyword(s):  
3D Reconstruction ◽  
Structured Light ◽  
Target Surface ◽  
Point Clouds ◽  
Single Shot ◽  
Camera Systems ◽  
3D Point Clouds ◽  
Random Arrays ◽  
Dense 3D Reconstruction

Structured Light (SL) patterns generated based on pseudo-random arrays are widely used for single-shot 3D reconstruction using projector-camera systems. These SL images consist of a set of tags with different appearances, where these patterns will be projected on a target surface, then captured by a camera and decoded. The precision of localizing these tags from captured camera images affects the quality of the pixel-correspondences between the projector and the camera, and consequently that of the derived 3D shape. In this paper, we incorporate a quadrilateral representation for the detected SL tags that allows the construction of robust and accurate pixel-correspondences and the application of a spatial rectification module that leads to high tag classification accuracy. When applying the proposed method to single-shot 3D reconstruction, we show the effectiveness of this method over a baseline in estimating denser and more accurate 3D point-clouds.

Single-shot 3D reconstruction imaging approach based on polarization properties of reflection lights

2021 ◽  
Author(s):  
Feiya Ma ◽  
Fang Wang ◽  
Rui Yang ◽  
Jian Liang ◽  
Liyong Ren
Keyword(s):  
3D Reconstruction ◽  
Single Shot ◽  
Imaging Approach

A low-cost 3D reconstruction system using a single-shot projection of a pattern matrix

2011 ◽  
Vol 26 (133) ◽  
pp. 91-110 ◽  
Author(s):  
Mário L. L. Reiss ◽  
Antonio M. G. Tommaselli
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Single Shot ◽  
Pattern Matrix

Detection, Averaging, and 3D Reconstruction of Biological Specimens on Hypercubes (Transputer-based) Computers

1990 ◽  
Vol 48 (1) ◽  
pp. 454-455
Author(s):  
Jose-Maria Carazo ◽  
I. Benavides ◽  
S. Marco ◽  
J.L. Carrascosa ◽  
E.L. Zapata
Keyword(s):  
3D Reconstruction ◽  
3D Structure ◽  
Three Dimensional ◽  
Software Tools ◽  
Mapping Method ◽  
Computer Architectures ◽  
Parallel Computer ◽  
Reconstruction Process ◽  
Computing Power ◽  
Order Of Magnitude

Obtaining the three-dimensional (3D) structure of negatively stained biological specimens at a resolution of, typically, 2 - 4 nm is becoming a relatively common practice in an increasing number of laboratories. A combination of new conceptual approaches, new software tools, and faster computers have made this situation possible. However, all these 3D reconstruction processes are quite computer intensive, and the middle term future is full of suggestions entailing an even greater need of computing power. Up to now all published 3D reconstructions in this field have been performed on conventional (sequential) computers, but it is a fact that new parallel computer architectures represent the potential of order-of-magnitude increases in computing power and should, therefore, be considered for their possible application in the most computing intensive tasks.We have studied both shared-memory-based computer architectures, like the BBN Butterfly, and local-memory-based architectures, mainly hypercubes implemented on transputers, where we have used the algorithmic mapping method proposed by Zapata el at. In this work we have developed the basic software tools needed to obtain a 3D reconstruction from non-crystalline specimens (“single particles”) using the so-called Random Conical Tilt Series Method. We start from a pair of images presenting the same field, first tilted (by ≃55°) and then untilted. It is then assumed that we can supply the system with the image of the particle we are looking for (ideally, a 2D average from a previous study) and with a matrix describing the geometrical relationships between the tilted and untilted fields (this step is now accomplished by interactively marking a few pairs of corresponding features in the two fields). From here on the 3D reconstruction process may be run automatically.

Sign in / Sign up

Export Citation Format

Share Document