Kinect-Based Universal Range Sensor for Laboratory Experiments

The Microsoft Kinect is part of a wave of new sensing technologies. Its RGB-D camera is capable of providing high quality synchronized video of both color and depth data. Compared to traditional 3-D tracking techniques that use two separate RGB cameras’ images to calculate depth data, the Kinect is able to produce more robust and reliable results in object recognition and motion tracking. Also, due to its low cost, the Kinect provides more opportunities for use in many areas compared to traditional more expensive 3-D scanners. In order to use the Kinect as a range sensor, algorithms must be designed to first recognize objects of interest and then track their motions. Although a large number of algorithms for both 2-D and 3-D object detection have been published, reliable and efficient algorithms for 3-D object motion tracking are rare, especially using Kinect as a range sensor. In this paper, algorithms for object recognition and tracking that can make use of both RGB and depth data in different scenarios are introduced. Subsequently, efficient methods for scene segmentation including background and noise filtering are discussed. Taking advantage of those two kinds of methods, a prototype system that is capable of working efficiently and stably in various applications related to educational laboratories is presented.

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A Platform for Mechanical Assembly Education Using the Microsoft Kinect

Volume 5: Education and Globalization ◽

10.1115/imece2014-38606 ◽

2014 ◽

Cited By ~ 4

Author(s):

Yizhe Chang ◽

El-Sayed Aziz ◽

Zhou Zhang ◽

Mingshao Zhang ◽

Sven Esche ◽

...

Keyword(s):

Undergraduate Students ◽

Computer Aided Design ◽

Motion Tracking ◽

Low Cost ◽

Financial Burden ◽

Human Motion ◽

Microsoft Kinect ◽

Input Device ◽

Mechanical Assembly ◽

Mechanical Parts

Mechanical assembly activities involve multiple factors including humans, mechanical parts, tools and assembly environments. In order to simulate assembly processes by computers for educational purposes, all these factors should be considered. Virtual reality (VR) technology, which aims to integrate natural human motion into real-world scenarios, provides an ideal simulation medium. Novel VR devices such as 3D glasses, motion-tracking gloves, haptic sensors, etc. are able to fulfill fundamental assembly simulation needs. However, most of these implementations focus on assembly simulations for computer-aided design, which are geared toward professionals rather than students, thus leading to complicated assembly procedures not suitable for students. Furthermore, the costs of these novel VR devices and specifically designed VR platforms represent an untenable financial burden for most educational institutions. In this paper, a virtual platform for mechanical assembly education based on the Microsoft Kinect sensor and Garry’s Mod (GMod) is presented. With the help of the Kinect’s body tracking function and voice recognition technology in conjunction with the graphics and physics simulation capabilities of GMod, a low-cost VR platform that enables educators to author their own assembly simulations was implemented. This platform utilizes the Kinect as the sole input device. Students can use voice commands to navigate their avatars inside of a GMod powered virtual laboratory as well as use their body’s motions to integrate pre-defined mechanical parts into assemblies. Under this platform, assembly procedures involving the picking, placing and attaching of parts can be performed collaboratively by multiple users. In addition, the platform allows collaborative learning without the need for the learners to be co-located. A pilot study for this platform showed that, with the instructor’s assistance, mechanical engineering undergraduate students are able to complete basic assembly operations.

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AZURE KINECT BODY TRACKING UNDER REVIEW FOR THE SPECIFIC CASE OF UPPER LIMB EXERCISES

MM Science Journal ◽

10.17973/mmsj.2021_6_2021012 ◽

2021 ◽

Vol 2021 (2) ◽

pp. 4333-4341

Author(s):

EUGENIO IVORRA ◽

◽

MARIO ORTEGA ◽

MARIANO ALCANIZ

Keyword(s):

Upper Limb ◽

Pose Estimation ◽

Motion Tracking ◽

Tracking System ◽

Low Cost ◽

Pearson Correlation ◽

Microsoft Kinect ◽

Estimation Methods ◽

Body Tracking ◽

Human Pose

A tool for human pose estimation and quantification using consumer-level equipment is a long-pursued objective. Many studies have employed the Microsoft Kinect v2 depth camera but with recent release of the new Kinect Azure a revision is required. This work researches the specific case of estimating the range of motion in five upper limb exercises using four different pose estimation methods. These exercises were recorded with the Kinect Azure camera and assessed with the OptiTrack motion tracking system as baseline. The statistical analysis consisted of evaluation of intra-rater reliability with intra-class correlation, the Pearson correlation coefficient and Bland–Altman statistical procedure. The modified version of the OpenPose algorithm with the post-processing algorithm PoseFix had excellent reliability with most intra-class correlations being over 0.75. The Azure body tracking algorithm had intermediate results. The results obtained justify clinicians employing these methods, as quick and low-cost simple tools, to assess upper limb angles.

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A Low-Cost, High Quality MRI Breast Scanner Using Prepolarization

10.21236/ada390614 ◽

1999 ◽

Author(s):

Albert Macovski

Keyword(s):

Low Cost ◽

High Quality

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Concentration of Impurities during Melting of Snow Made from Secondary Sewage Effluent

Water Science & Technology ◽

10.2166/wst.1986.0024 ◽

1986 ◽

Vol 18 (2) ◽

pp. 151-156 ◽

Cited By ~ 4

Author(s):

R. Zapf-Gilje ◽

S. O. Russell ◽

D. S. Mavinic

Keyword(s):

Potassium Chloride ◽

Chloride Solution ◽

Laboratory Experiments ◽

Field Experiments ◽

Low Cost ◽

Sewage Effluent ◽

Potassium Chloride Solution ◽

Laboratory Results ◽

Solution Field ◽

Concentration Of Impurities

When snow is made from sewage effluent, the impurities become concentrated in the early melt leaving the later runoff relatively pure. This could provide a low cost method of separating nutrients from secondary sewage effluent. Laboratory experiments showed that the degree of concentration was largely independent of the number of melt freeze cycles or initial concentration of impurity in the snow. The first 20% of melt removed with it 65% of the phosphorus and 90% of the nitrogen from snow made from sewage effluent; and over 90% of potassium chloride from snow made from potassium chloride solution. Field experiments with a salt solution confirmed the laboratory results.

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Low-cost synthesis of high quality graphene oxide with large electrical and thermal conductivities

Materials Letters ◽

10.1016/j.matlet.2021.129649 ◽

2021 ◽

pp. 129649

Author(s):

Shalik Ram Joshi ◽

Jaekyo Lee ◽

Gun-Ho Kim

Keyword(s):

Graphene Oxide ◽

Low Cost ◽

High Quality ◽

Thermal Conductivities

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An Anti-Counterfeiting Architecture for Traceability System Based on Modified Two-Level Quick Response Codes

Electronics ◽

10.3390/electronics10030320 ◽

2021 ◽

Vol 10 (3) ◽

pp. 320

Author(s):

Shundao Xie ◽

Hong-Zhou Tan

Keyword(s):

Product Life Cycle ◽

Low Cost ◽

Prototype System ◽

Qr Code ◽

Quick Response ◽

Copy Detection ◽

Traceability System ◽

Scanned Image ◽

Promising Solution ◽

Product Package

Traceability is considered a promising solution for product safety. However, the data in the traceability system is only a claim rather than a fact. Therefore, the quality and safety of the product cannot be guaranteed since we cannot ensure the authenticity of products (aka counterfeit detection) in the real world. In this paper, we focus on counterfeit detection for the traceability system. The risk of counterfeiting throughout a typical product life cycle in the supply chain is analyzed, and the corresponding requirements for the tags, packages, and traceability system are given to eliminate these risks. Based on the analysis, an anti-counterfeiting architecture for traceability system based on two-level quick response codes (2LQR codes) is proposed, where the problem of counterfeit detection for a product is transformed into the problem of copy detection for the 2LQR code tag. According to the characteristics of the traceability system, the generation progress of the 2LQR code is modified, and there is a corresponding improved algorithm to estimate the actual location of patterns in the scanned image of the modified 2LQR code tag to improve the performance of copy detection. A prototype system based on the proposed architecture is implemented, where the consumers can perform traceability information queries by scanning the 2LQR code on the product package with any QR code reader. They can also scan the 2LQR code with a home-scanner or office-scanner, and send the scanned image to the system to perform counterfeit detection. Compared with other anti-counterfeiting solutions, the proposed architecture has advantages of low cost, generality, and good performance. Therefore, it is a promising solution to replace the existing anti-counterfeiting system.

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Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽

10.3390/atmos12010091 ◽

2021 ◽

Vol 12 (1) ◽

pp. 91

Author(s):

Santiago Lopez-Restrepo ◽

Andres Yarce ◽

Nicolás Pinel ◽

O.L. Quintero ◽

Arjo Segers ◽

...

Keyword(s):

Air Quality ◽

Data Assimilation ◽

Transport Model ◽

Cost Model ◽

Low Cost ◽

Model Performance ◽

Monitoring Network ◽

Correlation Factor ◽

Chemical Transport Model ◽

High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

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A V-SLAM Guided and Portable System for Photogrammetric Applications

Remote Sensing ◽

10.3390/rs13122351 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2351

Author(s):

Alessandro Torresani ◽

Fabio Menna ◽

Roberto Battisti ◽

Fabio Remondino

Keyword(s):

Low Cost ◽

Cost Effective ◽

Motion Blur ◽

Guidance System ◽

Prototype System ◽

Active Sensors ◽

Localization And Mapping ◽

Acquisition Speed ◽

Mobile Mapping System ◽

Slam Algorithm

Mobile and handheld mapping systems are becoming widely used nowadays as fast and cost-effective data acquisition systems for 3D reconstruction purposes. While most of the research and commercial systems are based on active sensors, solutions employing only cameras and photogrammetry are attracting more and more interest due to their significantly minor costs, size and power consumption. In this work we propose an ARM-based, low-cost and lightweight stereo vision mobile mapping system based on a Visual Simultaneous Localization And Mapping (V-SLAM) algorithm. The prototype system, named GuPho (Guided Photogrammetric System) also integrates an in-house guidance system which enables optimized image acquisitions, robust management of the cameras and feedback on positioning and acquisition speed. The presented results show the effectiveness of the developed prototype in mapping large scenarios, enabling motion blur prevention, robust camera exposure control and achieving accurate 3D results.

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