scholarly journals Depth Measurement Based on Infrared Coded Structured Light

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Tong Jia ◽  
ZhongXuan Zhou ◽  
HaiHong Gao
Keyword(s):  
Linear Relationship ◽  
Measurement Accuracy ◽  
Step Length ◽  
Depth Information ◽  
Grid Pattern ◽  
Depth Measurement ◽  
Object Based ◽  
Fitting Algorithm ◽  
Object Depth ◽  
System Errors

Depth measurement is a challenging problem in computer vision research. In this study, we first design a new grid pattern and develop a sequence coding and decoding algorithm to process the pattern. Second, we propose a linear fitting algorithm to derive the linear relationship between the object depth and pixel shift. Third, we obtain depth information on an object based on this linear relationship. Moreover, 3D reconstruction is implemented based on Delaunay triangulation algorithm. Finally, we utilize the regularity of the error curves to correct the system errors and improve the measurement accuracy. The experimental results show that the accuracy of depth measurement is related to the step length of moving object.

scholarly journals Target Image Matching Algorithm Based on Binocular CCD Ranging

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Dongming Li ◽  
Wei Su ◽  
Jinhua Yang ◽  
Lijuan Zhang
Keyword(s):  
Measurement Accuracy ◽  
Experimental Results ◽  
Target Image ◽  
Actual Measurement ◽  
Matching Algorithm ◽  
Cubic Surface ◽  
Fitting Algorithm ◽  
Surface Fitting Algorithm ◽  
System Errors ◽  
Correlation Matching

This paper proposed target image in a subpixel level matching algorithm for binocular CCD ranging, which is based on the principle of binocular CCD ranging. In the paper, firstly, we introduced the ranging principle of the binocular ranging system and deduced a binocular parallax formula. Secondly, we deduced the algorithm which was named improved cross-correlation matching algorithm and cubic surface fitting algorithm for target images matched, and it could achieve a subpixel level matching for binocular CCD ranging images. Lastly, through experiment we have analyzed and verified the actual CCD ranging images, then analyzed the errors of the experimental results and corrected the formula of calculating system errors. Experimental results showed that the actual measurement accuracy of a target within 3 km was higher than 0.52%, which meet the accuracy requirements of the high precision binocular ranging.

scholarly journals Validation of a Laser Ranged Scanner-Based Detection of Spatio-Temporal Gait Parameters Using the aTUG Chair

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1343
Author(s):  
Sebastian Fudickar ◽  
Jörn Kiselev ◽  
Christian Stolle ◽  
Thomas Frenken ◽  
Elisabeth Steinhagen-Thiessen ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Measurement Accuracy ◽  
Dynamic Balance ◽  
Step Length ◽  
Berg Balance Scale ◽  
Walking Ability ◽  
Functional Requirements ◽  
Balance Confidence ◽  
Gait Parameters ◽  
Abc Scale

This article covers the suitability to measure gait-parameters via a Laser Range Scanner (LRS) that was placed below a chair during the walking phase of the Timed Up&Go Test in a cohort of 92 older adults (mean age 73.5). The results of our study demonstrated a high concordance of gait measurements using a LRS in comparison to the reference GAITRite walkway. Most of aTUG’s gait parameters demonstrate a strong correlation coefficient with the GAITRite, indicating high measurement accuracy for the spatial gait parameters. Measurements of velocity had a correlation coefficient of 99%, which can be interpreted as an excellent measurement accuracy. Cadence showed a slightly lower correlation coefficient of 96%, which is still an exceptionally good result, while step length demonstrated a correlation coefficient of 98% per leg and stride length with an accuracy of 99% per leg. In addition to confirming the technical validation of the aTUG regarding its ability to measure gait parameters, we compared results from the GAITRite and the aTUG for several parameters (cadence, velocity, and step length) with results from the Berg Balance Scale (BBS) and the Activities-Specific Balance Confidence-(ABC)-Scale assessments. With confidence coefficients for BBS and velocity, cadence and step length ranging from 0.595 to 0.798 and for ABC ranging from 0.395 to 0.541, both scales demonstrated only a medium-sized correlation. Thus, we found an association of better walking ability (represented by the measured gait parameters) with better balance (BBC) and balance confidence (ABC) overall scores via linear regression. This results from the fact that the BBS incorporates both static and dynamic balance measures and thus, only partly reflects functional requirements for walking. For the ABC score, this effect was even more pronounced. As this is to our best knowledge the first evaluation of the association between gait parameters and these balance scores, we will further investigate this phenomenon and aim to integrate further measures into the aTUG to achieve an increased sensitivity for balance ability.

scholarly journals An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature

2017 ◽  
Author(s):  
Lixin He ◽  
Jing Yang ◽  
Bin Kong ◽  
Can Wang
Keyword(s):  
Automatic Measurement ◽  
Depth Estimation ◽  
Depth Information ◽  
Scale Invariant ◽  
Line Segments ◽  
Sift Feature ◽  
Novel Approach ◽  
Straight Line ◽  
Object Depth ◽  
Scale Invariant Feature

It is one of very important and basic problem in compute vision field that recovering depth information of objects from two-dimensional images. In view of the shortcomings of existing methods of depth estimation, a novel approach based on SIFT (the Scale Invariant Feature Transform) is presented in this paper. The approach can estimate the depths of objects in two images which are captured by an un-calibrated ordinary monocular camera. In this approach, above all, the first image is captured. All of the camera parameters remain unchanged, and the second image is acquired after moving the camera a distance d along the optical axis. Then image segmentation and SIFT feature extraction are implemented on the two images separately, and objects in the images are matched. Lastly, an object depth can be computed by the lengths of a pair of straight line segments. In order to ensure that the best appropriate a pair of straight line segments are chose and reduce the computation, the theory of convex hull and the knowledge of triangle similarity are employed. The experimental results show our approach is effective and practical.

scholarly journals ENHANCED RGB-D MAPPING METHOD FOR DETAILED 3D MODELING OF LARGE INDOOR ENVIRONMENTS

2016 ◽  
Vol III-1 ◽  
pp. 151-158
Author(s):  
Shengjun Tang ◽  
Qing Zhu ◽  
Wu Chen ◽  
Walid Darwish ◽  
Bo Wu ◽  
...  
Keyword(s):  
3D Modeling ◽  
Visual Information ◽  
3D Models ◽  
Measurement Range ◽  
Mapping Method ◽  
Depth Information ◽  
Indoor Environments ◽  
Recovery Method ◽  
Depth Measurement ◽  
Rgb Image

RGB-D sensors are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks with respect to 3D dense mapping of indoor environments. First, they only allow a measurement range with a limited distance (e.g., within 3 m) and a limited field of view. Second, the error of the depth measurement increases with increasing distance to the sensor. In this paper, we propose an enhanced RGB-D mapping method for detailed 3D modeling of large indoor environments by combining RGB image-based modeling and depth-based modeling. The scale ambiguity problem during the pose estimation with RGB image sequences can be resolved by integrating the information from the depth and visual information provided by the proposed system. A robust rigid-transformation recovery method is developed to register the RGB image-based and depth-based 3D models together. The proposed method is examined with two datasets collected in indoor environments for which the experimental results demonstrate the feasibility and robustness of the proposed method

scholarly journals Vari-Focal Light Field Camera for Extended Depth of Field

Micromachines ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1453
Author(s):  
Hyun Myung Kim ◽  
Min Seok Kim ◽  
Sehui Chang ◽  
Jiseong Jeong ◽  
Hae-Gon Jeon ◽  
...  
Keyword(s):  
Light Field ◽  
High Reliability ◽  
Focal Length ◽  
Outdoor Environment ◽  
Depth Of Field ◽  
Depth Information ◽  
Single Shot ◽  
Depth Sensing ◽  
Depth Measurement ◽  
Sensing Applications

The light field camera provides a robust way to capture both spatial and angular information within a single shot. One of its important applications is in 3D depth sensing, which can extract depth information from the acquired scene. However, conventional light field cameras suffer from shallow depth of field (DoF). Here, a vari-focal light field camera (VF-LFC) with an extended DoF is newly proposed for mid-range 3D depth sensing applications. As a main lens of the system, a vari-focal lens with four different focal lengths is adopted to extend the DoF up to ~15 m. The focal length of the micro-lens array (MLA) is optimized by considering the DoF both in the image plane and in the object plane for each focal length. By dividing measurement regions with each focal length, depth estimation with high reliability is available within the entire DoF. The proposed VF-LFC is evaluated by the disparity data extracted from images with different distances. Moreover, the depth measurement in an outdoor environment demonstrates that our VF-LFC could be applied in various fields such as delivery robots, autonomous vehicles, and remote sensing drones.

scholarly journals Indoor Positioning Method Based on Wireless Signal

2018 ◽  
Vol 14 (10) ◽  
pp. 53
Author(s):  
Jingjing Yang ◽  
Zhenyu Feng ◽  
Xuchao Ma ◽  
Xiao Zhang
Keyword(s):  
Measurement Accuracy ◽  
Wave Attenuation ◽  
Indoor Positioning ◽  
Least Square ◽  
Font Size ◽  
Least Square Fitting ◽  
Fitting Algorithm ◽  
Wireless Signal ◽  
Positioning Method ◽  
Indoor Positioning System

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">In view of the problems of traditional wireless indoor positioning technologies such as errors and a low positioning accuracy that cannot reach the application level required by hospital indoor positioning, this study proposes a hospital indoor positioning method based on wireless signals. This study firstly analyzes the principles of hospital indoor positioning, verifies the reliability and accuracy of the collected data using Gaussian distribution, P-P plot and Q-Q plot, and finally analyzes the collected data using the least square fitting algorithm to obtain a fitting wave attenuation model, which is then applied to the indoor positioning system. Experiments show that this method can reduce the error of indoor positioning in hospitals, and improve the repeatability and measurement accuracy of indoor positioning in hospitals.</span>

Real-time depth measurement in glow discharge optical emission spectrometry via differential interferometric profiling

2017 ◽  
Vol 32 (9) ◽  
pp. 1798-1804 ◽  
Author(s):  
S. Gaiaschi ◽  
S. Richard ◽  
P. Chapon ◽  
O. Acher
Keyword(s):  
Glow Discharge ◽  
Real Time ◽  
Measurement Technique ◽  
Optical Emission ◽  
Optical Emission Spectrometry ◽  
Emission Spectrometry ◽  
Depth Information ◽  
Depth Measurement

We developed an in situ measurement technique implemented on a Glow Discharge Optical Emission Spectrometry (GD-OES) instrument, which provides the depth information during the profiling process.

scholarly journals Water Discharge and River Depth Measurement Using Fuzzy Logic Based on Internet of Things

2020 ◽  
Vol 4 (3) ◽  
pp. 384-391
Author(s):  
Kurnia Wisuda Aji ◽  
Aji Gautama Putrada ◽  
Sidik Prabowo ◽  
Mas'ud Adhi Saputra
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Real Time ◽  
Water Flow ◽  
Water Discharge ◽  
Ultrasonic Sensor ◽  
Flow Sensor ◽  
Depth Information ◽  
Sufficient Information ◽  
Depth Measurement

Based on statistics from Indonesian National Board for Disaster Management (BNPB) there are still many casualties caused by drifting or drowning in rivers every year. This is because most victims do not have sufficient information related to water discharge and river depth. In an effort to reduce the potential victims of these problems, a prototype was designed to provide a warning regarding river status as a display in the detail condition of the river in real-time. In this research, a prototype measuring instrument was produced that could provide information on water discharge and river depth in a sustainable and real-time manner. The prototype device consists of two main sensors as an implementation of internet of things, a water flow sensor and an ultrasonic sensor. Water flow sensor used to calculate the water discharge, and ultrasonic sensor used to measure depth of the river. Fuzzy logic has been used because it can work well for simple classification and work similarly like human reasoning. This information can be monitored through the website and LCD attached on the device. The results of the study with the help of the Linear Congruential Generator (LCG) method indicated that greater input value of the water discharge and the river depth caused more dangerous of the river status. Whereas the prototype produced has an error range of 5-6 cm for depth information generated by the ultrasonic sensor while the accuracy of the water flow sensor on the master device is 79.75% and the slave device is 84%.  

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