https://github.com/harmanveer-2546/yoga-pose-estimation

Efficient yoga pose estimation is a critical enabler for enhancing precision and performance in wellness and fitness applications. Advancements in computer vision and machine learning are driving remarkable progress in this domain.
https://github.com/harmanveer-2546/yoga-pose-estimation

3d-graph body-tracking google-library matplotlib mediapipe mediapipe-pose mediapipe-pose-estimation opencv plotly pose-estimation yoga-poses

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Efficient yoga pose estimation is a critical enabler for enhancing precision and performance in wellness and fitness applications. Advancements in computer vision and machine learning are driving remarkable progress in this domain.

• Host: GitHub
• URL: https://github.com/harmanveer-2546/yoga-pose-estimation
• Owner: harmanveer-2546
• Created: 2024-06-30T19:58:23.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2024-06-30T20:25:34.000Z (6 months ago)
• Last Synced: 2024-07-04T16:21:26.212Z (6 months ago)
• Topics: 3d-graph, body-tracking, google-library, matplotlib, mediapipe, mediapipe-pose, mediapipe-pose-estimation, opencv, plotly, pose-estimation, yoga-poses
• Language: Jupyter Notebook
• Homepage:
• Size: 2.25 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# YOGA POSE ESTIMATION

 * Achieving precise yoga pose estimation

is crucial for providing accurate

feedback to practitioners. It enables

fine-grained analysis of body alignment

and posture, leading to improved

performance and reduced risk of injury.

* Cutting-edge technologies including

convolutional neural networks and multi-view

geometry is revolutionizing yoga pose

estimation. These advancements are driving

significant improvements in precision and

performance.

* Improving the real-time performance

of yoga pose estimation systems are

essential for seamless integration into

interactive applications and fitness

tracking devices. This requires

optimizing algorithms for speed and

accuracy.

* Accurate yoga pose estimation has diverse

applications in wellness monitoring,

rehabilitation, and personalized coaching. It

enables precise assessment of body movements

and alignment for effective guidance.

* Accurate yoga pose estimation faces

challenges such as occlusions varied

body shapes, and dynamic

movements. Overcoming these

challenges are essential for robust and

reliable pose recognition.

* The future of yoga pose estimation

holds promise for advancements in 3D

pose reconstruction, multi-modal

sensing, and context-aware analysis.

These developments will further

elevate precision and performance.