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HUMAN POSE ESTIMATION

Authors: Jayasri R;

HUMAN POSE ESTIMATION

Abstract

In "Human Pose Estimation" with integrated feedback mechanisms to assess and guide users in achieving correct poses. Utilizing advanced deep learning techniques in computer vision, the system swiftly detects key points on the human body and provides instant feedback on pose accuracy. Built on convolutional neural networks trained on extensive pose datasets, the system includes pose detection, classification, and feedback stages. By comparing detected poses with predefined correct poses, the system delivers positive feedback for accurate poses and corrective guidance for deviations. Key Words: Human Pose Estimation, Pose Detection, Pose Classification, Correct Pose Assessment, Fitness Training, Key Points Detection, Correct Pose Thresholds

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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