Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning
Abstract & Details
Research Area
COMPUTER ENGINEERING AND INFORMATION TECHNOLOGY
Keywords
DEEP LEARNING
FACIAL RECOGNITION
CONVOLUTIONAL NEURAL NETWORK
STRESS DETECTION
OPENCV
Abstract
This paper endeavours to increase a actual-time facial reputation gadget for non-intrusive pressure detection utilizing the synergies of opencv and deep analyzing methodologies the primary aim is to create a precise and inexperienced device that respects patron consolation while empowering individuals with immediately stress manage competencies the devices objectives encompass because it must be detecting strain tiers via facial popularity enforcing actual-time facial picture seize thru the use of a web virtual digital camera leveraging opencvs haar cascade for strong face detection and integrating a pre-knowledgeable convolutional neural network cnn model for strain estimation the proposed work consists of shooting facial pictures thru an internet digital camera making use of opencvs haar cascade for face detection and processing remoted faces with a meticulously skilled cnn model this --step technique complements the accuracy of pressure diploma checks via figuring out nuanced facial cues indicative of stress the ensuing gadget stands at the intersection of pc innovative prescient and intellectual health technology presenting a bendy and mighty solution for pressure monitoring and nicely-being projects this system addresses the crucial issue of real-time stress detection the usage of non-invasive techniques pressure is a challenge in cutting-edge existence exacerbated by means of elements consisting of the covid pandemic the assignment is steady with the findings of the literature review which emphasize the significance of non-invasive pressure detection strategies including imaging strategies the proposed real-time face reputation algorithm sticks out by combining the talents of opencv with deep learning the opencv haar cascade improves face popularity while the mixed cnn model will increase the accuracy of pressure estimation an emphasis on consolation as a consumer makes the device non-intrusive and respectful of person privacy the literature assessment well-knownshows various techniques for stress detection along with picture-primarily based biosignal machine gaining knowledge of with face masks and deep gaining knowledge of with defeat cascade algorithms these research provide insights precious in phrases of the processes and demanding situations associated with stress popularity the significance of the program extends beyond technological innovation aiming to help boost attention of mental health and nicely-being by supplying people with on the spot strain remedy this system aligns with the wider goal of enhancing intellectual fitness thru era in end the real-time facial recognition assignment for non-invasive human strain detection combines contemporary era with a holistic approach to deal with an important thing of human nicely-being thru diligent implementation and pursuit of specific targets the venture aims to have a significant impact on strategies of strain detection pc imaginative and prescient and mental health technologies
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | RITHIKAA K | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
| 2 | KISHORE V | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
| 3 | MR.SATHEESH N P | BANNARI AMMAN INSTITUTE OF TECHNOLOGY |
How to Cite
Use the following formats to cite this article in your research.
APA Style
K, RITHIKAA, V, KISHORE, & P, MR.SATHEESH N (2024). Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning. International Journal of Advance Research and Innovative Ideas In Education, 10(1), 1154-1159.
MLA Style
K, RITHIKAA, et al. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 1, 2024, pp. 1154-1159.
IEEE Style
RITHIKAA K, KISHORE V, and MR.SATHEESH N P, "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 1, pp. 1154-1159, 2024.
Vancouver Style
K RITHIKAA, V KISHORE, P MR.SATHEESH N. Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(1):1154-1159.
Harvard Style
K, RITHIKAA, V, KISHORE, & P, MR.SATHEESH N (2024) 'Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning', International Journal of Advance Research and Innovative Ideas In Education, 10(1), pp. 1154-1159.
Chicago Style
K, RITHIKAA, KISHORE V, and MR.SATHEESH N P. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning." International Journal of Advance Research and Innovative Ideas In Education 10, no. 1 (2024): 1154-1159.
Turabian Style
K, RITHIKAA, KISHORE V, and MR.SATHEESH N P. "Real-Time Facial Recognition for Non-Intrusive Human Stress Detection using OpenCV and Deep Learning." International Journal of Advance Research and Innovative Ideas In Education 10, no. 1 (2024): 1154-1159.
Related Research
AI-Based Personalized Learning Recommendation System
PDF Unavailable
Rethinking Evidence Production in the Age of Artificial Intelligence: An IMRaD Perspective on Statistical Reasoning in Data Analysis
PDF Unavailable
PCE IT ASSISTANT APPLICATION (An Educational RAG App)
PDF Unavailable
Virtual Assistants for Blind and Visually Impaired People: A Review of Technologies, Applications, and Challenges
PDF Unavailable
AI Based Resume Scanner
PDF Unavailable