Paper Title
BODY LAUNGUAGE DETECTION USING MACHINE LEARNING
Article Identifiers
: Authors
Keywords
Real-time Body Language Analysis, Webcam-based Pose, Classification Deep Learning Techniques ,Human-Machine Interaction Revolution, Communication Analysis Technology
Abstract
We present a overall solution for real-time body language analysis and pose classification. This innovative platform harnesses webcam technology to seamlessly capture and process video data, conducting whole-body estimation and precise joint coordinate collection at specified intervals. Through the adept application of deep learning techniques, we have cultivated an advanced pose classification model capable of discerning and accurately interpreting a wide spectrum of human poses and body language cues. This model empowers our system to uncover the subtleties in postures and movements, enabling it to identify and interpret emotions, intentions, and interactions without the need for verbal communication. By seamlessly integrating machine learning and computer vision, we unlock invaluable insights encoded within body language, rendering it a versatile tool for applications like communication analysis, human-computer interaction, and emotion recognition. This transformative system holds the promise to revolutionize multiple industries, spanning healthcare, education, security, and entertainment, thereby enhancing human-machine interaction and understanding on a profound level.
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How To Cite (APA)
Chaudhari Prathamesh Nitin, Bhosle Mahesh Sanjayrao, Shevkar Yash Sunil, & Jagtap Rahul Santosh (November-2023). BODY LAUNGUAGE DETECTION USING MACHINE LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(11), b355-b358. https://ijnrd.org/papers/IJNRD2311146.pdf
Issue
Volume 8 Issue 11, November-2023
Pages : b355-b358
Other Publication Details
Paper Reg. ID: IJNRD_208739
Published Paper Id: IJNRD2311146
Downloads: 000122253
Research Area: Engineering
Author Type: Indian Author
Country: pune, Maharashtra, india
Published Paper PDF: https://ijnrd.org/papers/IJNRD2311146.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2311146
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