scholarly journals Real-Time Efficient Relocation Algorithm Based on Depth Map for Small-Range Textureless 3D Scanning

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3855
Author(s):  
Fengbo Zhu ◽  
Shunyi Zheng ◽  
Xiaonan Wang ◽  
Yuan He ◽  
Li Gui ◽  
...  

As an important part of industrial 3D scanning, a relocation algorithm is used to restore the position and the pose of a 3D scanner or to perform closed-loop detection. The real time and the relocation correct ratio are prominent and difficult points in 3D scanning relocation research. By utilizing the depth map information captured by a binocular vision 3D scanner, we developed an efficient and real-time relocation algorithm to estimate the current position and pose of the sensor real-time and high-correct-rate relocation algorithm for small-range 3D texture less scanning. This algorithm mainly involves feature calculation, feature database construction and query, feature matching verification, and rigid transformation calculation; through the four parts, the initial position and pose of the sensors in the global coordinate system is obtained. In the experiments, the efficiency and the correct-rate of the proposed relocation algorithm were elaborately verified by offline and online experiments on four objects of different sizes, and a smooth and a rough surface. With more data frames and feature points, the relocation could be maintained real time within 200 ms, and a high correct rate of more than 90% could be realized. The experimental results showed that the proposed algorithm could achieve a real-time and high-correct-ratio relocation.

2018 ◽  
Vol 62 (4) ◽  
pp. 107-116
Author(s):  
Adrián Mezei ◽  
Tibor Kovács

Three-dimensional objects can be scanned by 3D laser scanners that use active triangulation. These scanners create three-dimensional point clouds from the scanned objects. The laser line is identified in the images, which are captured at given transformations by the camera, and the point cloud can be calculated from these. The hardest challenge is to construct these transformations so that most of the surface can be captured. The result of a scanning may have missing parts because either not the best transformations were used or because some parts of the object cannot be scanned. Based on the results of the previous scans, a better transformation plan can be created, with which the next scan can be performed. In this paper, a method is proposed for transforming a special 3D scanner into a position from where the scanned point can be seen from an ideal angle. A method is described for estimating this transformation in real-time, so these can be calculated for every point of a previous scan to set up a next improved scan.


Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 546
Author(s):  
Zhenni Li ◽  
Haoyi Sun ◽  
Yuliang Gao ◽  
Jiao Wang

Depth maps obtained through sensors are often unsatisfactory because of their low-resolution and noise interference. In this paper, we propose a real-time depth map enhancement system based on a residual network which uses dual channels to process depth maps and intensity maps respectively and cancels the preprocessing process, and the algorithm proposed can achieve real-time processing speed at more than 30 fps. Furthermore, the FPGA design and implementation for depth sensing is also introduced. In this FPGA design, intensity image and depth image are captured by the dual-camera synchronous acquisition system as the input of neural network. Experiments on various depth map restoration shows our algorithms has better performance than existing LRMC, DE-CNN and DDTF algorithms on standard datasets and has a better depth map super-resolution, and our FPGA completed the test of the system to ensure that the data throughput of the USB 3.0 interface of the acquisition system is stable at 226 Mbps, and support dual-camera to work at full speed, that is, 54 fps@ (1280 × 960 + 328 × 248 × 3).


2021 ◽  
pp. 129883
Author(s):  
Ahmad Aminzadeh ◽  
Sasan Sattarpanah Karganroudi ◽  
Noureddine Barka ◽  
Abderrazak El Ouafi
Keyword(s):  

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Jerzy Montusiewicz ◽  
Marek Miłosz ◽  
Jacek Kęsik ◽  
Kamil Żyła

AbstractHistorical costumes are part of cultural heritage. Unlike architectural monuments, they are very fragile, which exacerbates the problems of their protection and popularisation. A big help in this can be the digitisation of their appearance, preferably using modern techniques of three-dimensional representation (3D). The article presents the results of the search for examples and methodologies of implementing 3D scanning of exhibited historical clothes as well as the attendant problems. From a review of scientific literature it turns out that so far practically no one in the world has made any methodical attempts at scanning historical clothes using structured-light 3D scanners (SLS) and developing an appropriate methodology. The vast majority of methods for creating 3D models of clothes used photogrammetry and 3D modelling software. Therefore, an innovative approach was proposed to the problem of creating 3D models of exhibited historical clothes through their digitalisation by means of a 3D scanner using structural light technology. A proposal for the methodology of this process and concrete examples of its implementation and results are presented. The problems related to the scanning of 3D historical clothes are also described, as well as a proposal how to solve them or minimise their impact. The implementation of the methodology is presented on the example of scanning elements of the Emir of Bukhara's costume (Uzbekistan) from the end of the nineteenth century, consisting of the gown, turban and shoes. Moreover, the way of using 3D models and information technologies to popularise cultural heritage in the space of digital resources is also discussed.


Author(s):  
Jop Vermeer ◽  
Leonardo Scandolo ◽  
Elmar Eisemann

Ambient occlusion (AO) is a popular rendering technique that enhances depth perception and realism by darkening locations that are less exposed to ambient light (e.g., corners and creases). In real-time applications, screen-space variants, relying on the depth buffer, are used due to their high performance and good visual quality. However, these only take visible surfaces into account, resulting in inconsistencies, especially during motion. Stochastic-Depth Ambient Occlusion is a novel AO algorithm that accounts for occluded geometry by relying on a stochastic depth map, capturing multiple scene layers per pixel at random. Hereby, we efficiently gather missing information in order to improve upon the accuracy and spatial stability of conventional screen-space approximations, while maintaining real-time performance. Our approach integrates well into existing rendering pipelines and improves the robustness of many different AO techniques, including multi-view solutions.


2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Samy Bakheet ◽  
Ayoub Al-Hamadi

AbstractRobust vision-based hand pose estimation is highly sought but still remains a challenging task, due to its inherent difficulty partially caused by self-occlusion among hand fingers. In this paper, an innovative framework for real-time static hand gesture recognition is introduced, based on an optimized shape representation build from multiple shape cues. The framework incorporates a specific module for hand pose estimation based on depth map data, where the hand silhouette is first extracted from the extremely detailed and accurate depth map captured by a time-of-flight (ToF) depth sensor. A hybrid multi-modal descriptor that integrates multiple affine-invariant boundary-based and region-based features is created from the hand silhouette to obtain a reliable and representative description of individual gestures. Finally, an ensemble of one-vs.-all support vector machines (SVMs) is independently trained on each of these learned feature representations to perform gesture classification. When evaluated on a publicly available dataset incorporating a relatively large and diverse collection of egocentric hand gestures, the approach yields encouraging results that agree very favorably with those reported in the literature, while maintaining real-time operation.


2014 ◽  
Author(s):  
Kazuki Matsumoto ◽  
Chiyoung Song ◽  
Francois de Sorbier ◽  
Hideo Saito
Keyword(s):  

2021 ◽  
pp. 101-107
Author(s):  
Mohammad Alshehri ◽  

Presently, a precise localization and tracking process becomes significant to enable smartphone-assisted navigation to maximize accuracy in the real-time environment. Fingerprint-based localization is the commonly available model for accomplishing effective outcomes. With this motivation, this study focuses on designing efficient smartphone-assisted indoor localization and tracking models using the glowworm swarm optimization (ILT-GSO) algorithm. The ILT-GSO algorithm involves creating a GSO algorithm based on the light-emissive characteristics of glowworms to determine the location. In addition, the Kalman filter is applied to mitigate the estimation process and update the initial position of the glowworms. A wide range of experiments was carried out, and the results are investigated in terms of distinct evaluation metrics. The simulation outcome demonstrated considerable enhancement in the real-time environment and reduced the computational complexity. The ILT-GSO algorithm has resulted in an increased localization performance with minimal error over the recent techniques.


2013 ◽  
Vol 278-280 ◽  
pp. 905-914
Author(s):  
Wen Tao Gu ◽  
Shao Kun Lei ◽  
Fang Li ◽  
Shao Wei Zhou

To meet the high real-time performance and high accuracy requirements of signal detection in the rail splicing process, this paper proposes a new type of magnetic grid rail splicing method based on accurately zeroing output signal phase difference of two magnetic grid reading heads, thus establishing two reading heads “shift” rules. The accurate zero setting technology of phase difference is based on Nuttall window algorithm, which doesn’t need to give the exact signal frequency beforehand and sample periodically, and can effectively eliminate phase errors. So this algorithm is suitable for detecting signal phase difference when reading heads go over buff joints with any speed at any initial position. Additionally, simulation test and experimental verification were performed on this detection algorithm and “shift” rules. The results show that, the method mentioned in this paper can real-time detect the phase difference by “shift” rules, when reading heads go over buff joints with any speed or any acceleration.


2016 ◽  
Vol 62 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Adam Chromy

Abstract This paper deals with application of 3D scanning technology in medicine. Important properties of 3D scanners are discussed with emphasize on medical applications. Construction of medical 3D scanner according to these specifications is described and practical application of its use in medical volumetry is presented. Besides volumetry, such 3D scanner is usable for many other purposes, like monitoring of recovery process, ergonomic splint manufacturing or inflammation detection. 3D scanning introduces novel volumetric method, which is compared with standard methods. The new method is more accurate compared to present ones. Principles of this method are discussed in paper and its accuracy is evaluated and experimentally verified.


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