Sit up Straight! This extension will help you track your posture as you browse with the help of your webcam and Tensorflow.js

MoveNetを用いたPythonでの姿勢推定のデモ

This project focuses on Human Pose Estimation using the MoveNet model with TensorFlow Lite. The goal is to detect keypoint positions on a person's body in images and live video frames. The project provides a Flask web application for both image and live video input, showcasing the real-time capabilities of the model.

A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.

Application of Movenet model to detect multiple persons in a frame using convolutional neural network model

This is Pose Estimation project based on MoveNet architecture. It can detect the points so accurately and fast. And works for single pose estimation.

Posture Monitoring build on CNN & ANN using TensorflowJS and Movenet3 with client-side rendering

pose detection of a video with artificial agents

Pose Estimator using the fastest rendering MoveNet-Lightning framework with Tensorflow Lite.

Use Computer Vision and Deep Learning for Yoga training !

Simple web application analyzes user actions for video proctoring systems.

利用 AI 技術實現槍戰遊戲中輔助瞄準敵人的功能

Here we tried to detected different poses made by person using movenet/singlepose/lightning model

This system uses YOLO for object detection (specifically, garbage), MoveNet for hand landmark detection, and DeepFace for facial recognition. It analyzes the relationship between detected humans and garbage to identify potential littering incidents in real-time.

MoveNet-Web is a web application that leverages TensorFlow.js and the MoveNet model to perform real-time pose estimation directly in the browser. Built with Next.js and utilizing the WebGL backend, this application ensures efficient GPU acceleration for optimal performance.

This project develops a fall detection system using Pose Estimation and Optical Flow data with LSTM networks. It enhances detection accuracy for elderly care by analyzing body movements in real-time. Key technologies include the MoveNet model for pose estimation, Optical Flow analysis and LSTM networks for temporal analysis.