Low-cost electromyograph combined with markerless pose detection

2021 ◽  
Vol 88 (s1) ◽  
pp. s71-s76
Author(s):  
Florian Scheible ◽  
Raphael Lamprecht ◽  
Marc Rives ◽  
Alexander Sutor
Keyword(s):  
Computer Vision ◽  
Muscle Activity ◽  
Low Cost ◽  
Image Data ◽  
Knee Angle ◽  
Pose Detection ◽  
The Subject ◽  
Sample Rate ◽  
Good Agreement

Abstract This papers presents a low-cost electromyograph combined with marker-less pose detection using computer vision. The developed and build three channel electromyograph is tested by measuring the muscle activity of one leg, while the subject is performing squats. Simultaneously, a camera records the exercise and subsequently the image data is evaluated by OpenPose. We could show that this simple setup enables the user to evaluate the muscle activity of three independent muscles as function of the knee angle. These results are in good agreement to the expected muscle activity. The sample-rate of the EMG device is 2 kHz. The overall cost of the developed device is under 100 €. To our knowledge, this is the first work combining these two methods for dynamic exercises. The method is well customizable for other sports due to the battery powered device and its handy size.

FEASIBILITY ANALYSIS OF AN AUTOMATED DETECTION OF PHYSICAL DEFECT VIA COMPUTER VISION

2015 ◽  
Vol 76 (12) ◽  
Author(s):  
Por Jing Zhao ◽  
Shafriza Nisha Basah ◽  
Shazmin Aniza Abdul Shukor
Keyword(s):  
Computer Vision ◽  
Low Cost ◽  
Image Data ◽  
Automated Detection ◽  
Building Construction ◽  
High Demand ◽  
Major City ◽  
Cost System ◽  
Kinect Camera ◽  
Wall Condition

High demand of building construction has been taking places in the major city of Malaysia. However, despite this magnificent development, the lack of proper maintenance has caused a large portion of these properties deteriorated over time. The implementation of the project - Automated Detection of Physical Defect via Computer Vision - is a low cost system that helps to inspect the wall condition using Kinect camera. The system is able to classify the types of physical defects -crack and hole - and state its level of severity.The system uses artificial neural network as the image classifier due to its reliability and consistency. The validity of the system is shown using experiments on synthetic and real image data. This automated physical defect detection could detect building defect early, quickly, and easily, which results in cost saving and extending building life span. 

Image Capture Board for The PC

1995 ◽  
Vol 32 (3) ◽  
pp. 235-255
Author(s):  
T. David Binnie ◽  
I. Reading
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Personal Computer ◽  
Low Cost ◽  
Random Access ◽  
Image Data ◽  
Image Capture ◽  
Design And Implementation

Image capture board for the PC We report the design and implementation of a low cost, image capture board for an IBM type personal computer. The board is particularly suited to computer vision education. The board provides: image capture at video rate, random access to xy addressable image data, and options for on-board image processing hardware.

A LOW-COST RESISTIVIMETER FOR USE IN PRACTICAL LECTURES OF APPLIED GEOPHYSICS

2016 ◽  
Vol 34 (1) ◽  
Author(s):  
Walter Sydney Dutra Folly ◽  
Aracy Sousa Senra
Keyword(s):  
Electrical Resistivity ◽  
Low Cost ◽  
Test Area ◽  
Vertical Electrical Sounding ◽  
Applied Geophysics ◽  
Resistivity Profile ◽  
Electrical Sounding ◽  
Good Agreement

ABSTRACT. We describe the construction and testing of a simple and efficient low-cost resistivimeter designed for use in practical classes in Applied Geophysics. The equipment was successfully tested in a vertical electrical sounding (VES) performed on sandy terrain within the campus of the Universidade Federal de Sergipe, Brazil. The VES results were in good agreement with the profiles obtained from two boreholes located approximately 500 m from the test area, clearly demonstrating the efficiency of the equipment and the adopted methodology.Keywords: vertical electrical sounding, electrical resistivity, resistivity profile. RESUMO. Neste artigo, descrevemos a construção e o teste de um resistivímetro de baixo custo, simples e eficiente, concebido para ser utilizado em aulas práticas de Geofísica Aplicada. O equipamento foi testado com a realização de uma sondagem elétrica vertical (SEV) em um terreno arenoso localizado no campus da Universidade Federal de Sergipe, Brasil. Os resultados obtidos nesta SEV apresentaram boa concordância com os perfis observados em dois poços de sondagem localizados a 500 m da área de teste, fato que comprovou a eficiência do equipamento e da metodologia adotada.Palavras-chave: sondagem elétrica vertical, resistividade elétrica, perfil de resistividade. 

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

One Touch Workpiece Verification System for CNC Machining Using a Low-Cost Computer Vision Approach

2016 ◽  
Author(s):  
Maxwell K. Micali ◽  
Hayley M. Cashdollar ◽  
Zachary T. Gima ◽  
Mitchell T. Westwood
Keyword(s):  
Computer Vision ◽  
Low Cost ◽  
Cnc Machining ◽  
Potential Operator ◽  
Cnc Milling ◽  
Machining Processes ◽  
Loop Control ◽  
Operator Error ◽  
Verification System ◽  
Milling Machines

While CNC programmers have powerful tools to develop optimized toolpaths and machining plans, these efforts can be wholly undermined by something as simple as human operator error during fixturing. This project addresses that potential operator error with a computer vision approach to provide coarse, closed-loop control between fixturing and machining processes. Prior to starting the machining cycle, a sensor suite detects the geometry that is currently fixtured using computer vision algorithms and compare this geometry to a CAD reference. If the detected and reference geometries are not similar, the machining cycle will not start, and an alarm will be raised. The outcome of this project is the proof of concept of a low-cost, machine/controller agnostic solution that is applied to CNC milling machines. The Workpiece Verification System (WVS) prototype implemented in this work cost a total of $100 to build, and all of the processing is performed on the self-contained platform. This solution has additional applications beyond milling that the authors are exploring.

Kameraunterstützte Verschwendungsreduktion*/Computer-vision supported waste reduction in lean production

2017 ◽  
Vol 107 (09) ◽  
pp. 572-577
Author(s):  
B. Prof. Lorenz ◽  
I. Kaltenmark
Keyword(s):  
Computer Vision ◽  
Lean Manufacturing ◽  
Lean Production ◽  
Low Cost ◽  
Industrie 4.0 ◽  
Waste Reduction ◽  
Camera System ◽  
New Developments ◽  
Neue Entwicklungen

In modernen Produktionen ist Lean Manufacturing einer der wichtigsten Treiber für Produktivitätssteigerungen. Durch neue Entwicklungen im Bereich Industrie 4.0 können Impulse im Lean Manufacturing gegeben werden. An der OTH Regensburg wird getestet, wie kostengünstige Kamerasysteme helfen können, Verschwendungen sichtbar zu machen und zu minimieren. Es zeigt sich, dass auch mit geringen Investitionskosten neue Potentiale zur Verschwendungsreduktion aufgedeckt werden können.   In modern production lean manufacturing is one of the most effective drivers for productivity. Due to new developments in the Industrie 4.0-campaign new impulses can be given into lean manufacturing. Experiments at OTH Regensburg indicate that a low-cost camera system can help to make waste visible and minimize it. This shows that with low invest costs, new potentials for waste reduction can be revealed.

The State of Polydispersion of Hevea Latex. I

1946 ◽  
Vol 19 (1) ◽  
pp. 176-186
Author(s):  
J. H. E. Hessels
Keyword(s):  
Protein Content ◽  
Hevea Brasiliensis ◽  
The State ◽  
Rubber Content ◽  
Rubber Latex ◽  
Latex Particles ◽  
Rubber Particles ◽  
The Subject ◽  
Points Of View ◽  
Good Agreement

Abstract The rubber particles in the latex of Hevea brasiliensis are present in the form of a polydispersion, and their diameters lie within the range of 0.1 to 3 microns. The rubber hydrocarbon itself is composed of a mixture of macromolecules of different degrees of polymerization. Rubber latex is, therefore, a system which is at the same time both polydispersed and polymolecular. It is well known that the degree of dispersion of a substance governs to a great extent certain properties of the substance. Moreover, astonishing as it may seem, in the great number of investigations which have been made of the composition and properties of latex and crude rubber, almost no attention has been paid to the part which may be played by the dimensions of the latex particles. However, in an investigation concerned with the centrifugation of latex, Loomis and Stump have called attention to this possibility, and in a study of latex obtained by fractionation, and in which the majority of the latex particles were of large dimensions, McGavack came to the conclusion that the protein content is proportional to the surface area of the globules. This limited knowledge of the subject seemed to warrant a more thorough study of the problem, which is of fundamental importance both from the theoretical and practical points of view. The investigation as a whole divided itself into three essential parts: (1) separation of latex into fractions containing particles of different sizes, and measurement of the state of dispersion in these fractions, (2) a study of the relation of these fractions to the composition of the rubber, i.e., the relation between the content of nonrubber components and the size of the latex particles, and (3) a study of the changes in the properties of the rubber hydrocarbon with change in the size of the latex particles. The latex used in this investigation was ordinary latex, containing 38–40 per cent dry-rubber content and preserved with ammonia. For the most important points, a concentrated latex (creamed latex containing 60 per cent dry-rubber content) was also tested. These two latices were about two years old when the investigation was started, and they gave results which were in good agreement with each other. In the present paper, only the data obtained with the first of the two latices are presented.

scholarly journals MASHUP SCHEME DESIGN OF MAP TILES USING LIGHTWEIGHT OPEN SOURCE WEBGIS PLATFORM

2018 ◽  
Vol XLII-3 ◽  
pp. 565-571
Author(s):  
T. Hu ◽  
J. Fan ◽  
H. He ◽  
L. Qin ◽  
G. Li
Keyword(s):  
Coordinate System ◽  
Low Cost ◽  
Image Data ◽  
Source Image ◽  
Scheme Design ◽  
Paper Cover ◽  
Data Source ◽  
Single Data Source ◽  
Single Data ◽  
Loading Scheme

To address the difficulty involved when using existing commercial Geographic Information System platforms to integrate multi-source image data fusion, this research proposes the loading of multi-source local tile data based on CesiumJS and examines the tile data organization mechanisms and spatial reference differences of the CesiumJS platform, as well as various tile data sources, such as Google maps, Map World, and Bing maps. Two types of tile data loading schemes have been designed for the mashup of tiles, the single data source loading scheme and the multi-data source loading scheme. The multi-sources of digital map tiles used in this paper cover two different but mainstream spatial references, the WGS84 coordinate system and the Web Mercator coordinate system. According to the experimental results, the single data source loading scheme and the multi-data source loading scheme with the same spatial coordinate system showed favorable visualization effects; however, the multi-data source loading scheme was prone to lead to tile image deformation when loading multi-source tile data with different spatial references. The resulting method provides a low cost and highly flexible solution for small and medium-scale GIS programs and has a certain potential for practical application values. The problem of deformation during the transition of different spatial references is an important topic for further research.

scholarly journals PlantCV v2: Image analysis software for high-throughput plant phenotyping

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4088 ◽  
Author(s):  
Malia A. Gehan ◽  
Noah Fahlgren ◽  
Arash Abbasi ◽  
Jeffrey C. Berry ◽  
Steven T. Callen ◽  
...  
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Image Analysis ◽  
Image Data ◽  
Plant Phenotyping ◽  
Analysis Software ◽  
Computational Tools ◽  
Landmark Identification ◽  
Plant Image ◽  
Leaf Segmentation

Systems for collecting image data in conjunction with computer vision techniques are a powerful tool for increasing the temporal resolution at which plant phenotypes can be measured non-destructively. Computational tools that are flexible and extendable are needed to address the diversity of plant phenotyping problems. We previously described the Plant Computer Vision (PlantCV) software package, which is an image processing toolkit for plant phenotyping analysis. The goal of the PlantCV project is to develop a set of modular, reusable, and repurposable tools for plant image analysis that are open-source and community-developed. Here we present the details and rationale for major developments in the second major release of PlantCV. In addition to overall improvements in the organization of the PlantCV project, new functionality includes a set of new image processing and normalization tools, support for analyzing images that include multiple plants, leaf segmentation, landmark identification tools for morphometrics, and modules for machine learning.

scholarly journals Unified Framework for Vision Inference on the Edge

2020 ◽  
Author(s):  
Vysakh S Mohan
Keyword(s):  
Computer Vision ◽  
Mobile Robotics ◽  
Low Cost ◽  
Network Models ◽  
Ease Of Use ◽  
Use Cases ◽  
Unified Framework ◽  
Neural Network Models ◽  
Inference Models ◽  
Small Form Factor

Edge processing for computer vision systems enable incorporating visual intelligence to mobile robotics platforms. Demand for low power, low cost and small form factor devices are on the rise.This work proposes a unified platform to generate deep learning models compatible on edge devices from Intel, NVIDIA and XaLogic. The platform enables users to create custom data annotations,train neural networks and generate edge compatible inference models. As a testimony to the tools ease of use and flexibility, we explore two use cases — vision powered prosthetic hand and drone vision. Neural network models for these use cases will be built using the proposed pipeline and will be open-sourced. Online and offline versions of the tool and corresponding inference modules for edge devices will also be made public for users to create custom computer vision use cases.

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