Face Mask Detection Using OpenCV

Adusumalli, Harish; Kalyani, D.; Sri, R.Krishna; Pratapteja, M.; Rao, P. Venkateswara

doi:10.1109/icicv50876.2021.9388375

Cited by 59 publications

(22 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[7] Computer vision helps scholars to analyse images and video to obtain necessary information, understand information on events or descriptions, and scenic pattern. [13] It resembles giving the machine eyes and encouraging its mind to work as per what it can see.…”

Section: Journal Of Informatics Electrical and Electronicsmentioning

confidence: 99%

Media Control Using Hand Gestures

Singh¹,

Rizvi²

2021

J. Infor. Electr. Electron. Eng.

View full text Add to dashboard Cite

The corporate world today basically relies on presentations of ideas and statistics. In the board room, the presenters are highly conscious of depicting confidence in their presen-tation. This would entail accessibility and mobility to the presenter or media viewer. As the extent of Artificial Intelligence is increasing in all directions, I am utilizing its extreme capabilities to create a software that would help in accessibility and save time and money. This paper describes a software written in Python 3.8 and makes use of Python libraries like OpenCV and PyAutoGUI to receive input from the computer’s Webcam and recognize gestures to control the PowerPoint Presentation and Portable Document For-mat (PDF) files or the Media Control. The user interface is built with the Python library PyQt5. This paper aims are to help people control their Presentations and Portable Document Format (PDF) files, and many other media through their hand gestures, without using a mouse or any other pointing device. The software would not require any other external hardware; hence it would not burn a hole in people’s pockets.

show abstract

Section: Journal Of Informatics Electrical and Electronicsmentioning

confidence: 99%

Media Control Using Hand Gestures

Singh¹,

Rizvi²

2021

J. Infor. Electr. Electron. Eng.

View full text Add to dashboard Cite

show abstract

“…Kemudian dicari model AdaBoost yang optimum antara kompleksitas model yang rendah dengan performa model yang tinggi. Metode untuk melakukan pengenalan wajah sangat beragam, metode yang diusulkan adalah menggunakan haarcascade classifier pada OpenCV, OpenCV adalah pustaka sumber terbuka yang digunakan untuk aplikasi computer vision dalam mengidentifikasi pelacakan gerak, pengenalan wajah, deteksi objek, dan lain-lain [19].…”

Section: Pendahuluanunclassified

“…Haar Cascade adalah metode yang diajukan oleh Paul Viola dan dibangun oleh openCV untuk mengidentifikasi wajah seseorang. OpenCV adalah pustaka sumber terbuka yang digunakan untuk aplikasi computer vision dalam mengidentifikasi pelacakan gerak, pengenalan wajah, deteksi objek, dan lain-lain [19]. Salah satu cara untuk melakukan pendeteksian wajah yaitu dengan OpenCV.…”

Section: Haar Cascadeunclassified

Peningkatan Kinerja AMG8833 sebagai Thermocam dengan Metode Regresi AdaBoost untuk Pelaksanaan Protokol COVID-19

Iman

Putrada

Prabowo

et al. 2021

JETT

View full text Add to dashboard Cite

One way to prevent the spread of the COVID-19 virus is to check body temperature regularly. However, checking body temperature manually by directing the thermogun at someone's face is still often found. This study implements the use of the AMG8833 thermal camera to detect a person's body temperature without making any contact. The AMG8833 is a general-purpose temperature detection camera so to be used as a temperature meter, its accuracy needs to be improved by regression. The purpose of this research is to improve the performance of AMG833 as a thermal camera with AdaBoost regression. AdaBoost is a type of ensemble learning that uses several decision tree models. For face detection, the system uses the Haar Cascade method. The test results show that the decision tree model produces an R-Squared value of 0.93 and an RMSE of 0.21. Meanwhile, AdaBoost succeeded in improving the performance of the regression model with a higher R-Squared value and a lower RMSE value with values of 0.95 and 0.18, respectively.

show abstract

“…Both the latest technologies and algorithms are visible in the C++ GUI. Python, Java, and MATLAB/OCTAVE bindings are available [3]. Wrappers in a variety of programming languages have been created to promote broader acceptance.…”

Section: Opencv Librarymentioning

confidence: 99%

“…The main goal is to identify and comprehend the images and offer new images that are more useful for us in different life fieldsThe term "OpenCV" is an abbreviation for "open source computer vision." The architecture is made up of software, databases, and plugins that are pre-programmed with support for integrating computer vision applications [3]. It is one of the most used toolkits with a large developer group.…”

mentioning

confidence: 99%

Face Detection and Recognition Using Opencv

Suganthi¹,

Poongothai²,

Prashanthini³

et al. 2020

GOR

View full text Add to dashboard Cite

Computer Vision is one of the most fascinating and challenging tasks in the field of Artificial Intelligence. Computer Vision serves as a link between computer software and the visuals we see around us. It enables computer software to comprehend and learn about the visuals in its environment. As an example: The fruit is determined by its color, shape, and size. This job may seem simple for the human brain, but in the Computer Vision pipeline, we first collect data, then conduct data processing operations, and then train and educate the model to learn how to differentiate between fruits based on size, shape, and color. The main goal is to identify and comprehend the images and offer new images that are more useful for us in different life fieldsThe term "OpenCV" is an abbreviation for "open source computer vision." The architecture is made up of software, databases, and plugins that are pre-programmed with support for integrating computer vision applications [3]. It is one of the most used toolkits with a large developer group. It is well-known for the size at which it builds realworld usage cases for industrial use. OpenCV follows C/C++, Python, Java programming languages and can be used to build computer vision software for desktop and smartphone platforms such as Windows, Linux, macOS, Android, and iOS. The most recent releases are OpenCV-4.5.2 and OpenCV-3.4.14. It is free and open-source, as well as simple to use and install. It is intended for numerical productivity with a heavy emphasis on real-time applications. The first version was in the C programming language; however, its success increased with the release of Version 2.0, which had a C++ implementation [2]. C++ is used to create new features. OpenCV can be downloaded for free from http://opencv.org. This platform includes the most recent distribution update (version: 4.5.2) as well as older iterations. Photos must be in BGR or Grayscale format in order to be displayed or saved via OpenCV. Otherwise, unfavorable outcomes could occur [1].Face detection is a form of computer vision that aids in detecting and visualizing facial features in captured pictures or real-time videos. This type of object detection technique detects instances of semantic artifacts of a given class (such as people, cars, and houses) in digital pictures and videos. Face recognition has become increasingly important as technology has advanced, especially in fields such as photography, defense, and marketing [4], [5].

show abstract

Face Mask Detection Using OpenCV

Cited by 59 publications

References 18 publications

Media Control Using Hand Gestures

Media Control Using Hand Gestures

Peningkatan Kinerja AMG8833 sebagai Thermocam dengan Metode Regresi AdaBoost untuk Pelaksanaan Protokol COVID-19

Face Detection and Recognition Using Opencv

Contact Info

Product

Resources

About