Student Monitoring System for School Bus Using Facial Recognition

James, Ciya; Nettikadan, David

doi:10.1109/icoei.2019.8862534

Cited by 9 publications

(2 citation statements)

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“…It's a machine-learning-based method in which a cascade of actions is learned from a large number of positive and negative images. It becomes used to seeing things in different frames [12]. Fig.…”

Section: Haar Cascadementioning

confidence: 99%

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Face Detection and Recognition Using Opencv

Suganthi¹,

Poongothai²,

Prashanthini³

et al. 2020

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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].

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Section: Haar Cascadementioning

confidence: 99%

“…James and Nettikadan [12] introduced a system for monitoring in real-time inside school buses. By utilizing image processing, using an image to identify a student by a camera.…”

Section: Face Recognitionmentioning

confidence: 99%