C/C++/Python based computer vision models using OpenPose, OpenCV, DLIB, Keras and Tensorflow libraries. Object Detection, Tracking, Face Recognition, Gesture, Emotion and Posture Recognition

Detects the sitting position of a person

Posture recognition based on common camera

基于OpenPose的太极拳姿态识别系统

To help machines learn what we human beings are doing via a camera is important. Once it comes true, machines can make different responses to all kinds of human's postures. But the process is very difficult as well, because usually it is very slow and power-consuming, and requires a very large memory space. Here we focus on real-time posture recognition, and try to make the machine "know" what posture we make. The posture recognition system is consisted of DE10-Nano SoC FPGA Kit, a camera, and an HDMI monitor. SoC FPGA captures video streams from the camera, recognizes human postures with a CNN model, and finally shows the original video and classification result (standing, walking, waving, etc.) via HDMI interface.

Posture recognition for birds based on YOLOv8 keypoints regression. YOLOv8鸟类关键点姿态识别

Code for the paper "Fusing Body Posture with Facial Expressions for Joint Recognition of Affect in Child-Robot Interaction"

Recognize human posture from Kinect

Human Activities and Postural Transitions’ Recognition using Smartphone Data

Developing a Convolutional LSTM model for human posture recognition from wearable IMUs sensors

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This repo holds the code for our 3DV 2021 paper "Fusing Posture and Position Representations for Point Cloud-Based Hand Gesture Recognition"

Posture correction using computer vision and Mediapipe library enables the detection and correction of poor posture in images and live videos, promoting a healthier lifestyle in the digital era.

Posture-based Infant Action Recognition in the Wild with Very Limited Data (CVPRW2023)

Intelligent Volleyball posture recognition and correction

This project presents a fast and efficient technique for recognition of continuous hand gestures with a stationary background from video stream. The system consists of four modules- A real time hand tracking module, contour extraction module, tracker detection module, and gesture recognition. First of all, real-time hand tracking and extraction algorithm is applied to trace the moving hand and to extract the hand region, and then motion analysis is performed to characterize the temporal features. We then extract the tracker position from the image. This tracker posture is recognized as a hand gesture. Now it is matched with a set of pre-defined gestures to know its meaning. Before matching gesture, preprocessing is performed to remove other part of human body and to select only part of hand showing some useful gesture.

"MyPrivateCoach" is a software that assists users in indoor exercise through posture recognition developped with Unity.

An experiment of auto-aim mechanic for all FPS games using neural network and AI humanoid posture recognition. The main section of the code was not released. Discussion of anti-cheat only.

Simple program that can detect bad posture and alert.

Posture Recognition ML algorithms

IMU Accelerometer sensor dataset for Human Posture Recognition

A complete sitting posture recognition application using a OV5647 camera. Project carried out for the Internet of Things Course in July 2023.

Building a classifier for time series human activities. The goal is human activity recognition of simple activities and postural transitions with wearable sensor data.

Using the MPU-9250 IMU sensor, get the angle of a part of the body and visualize it with Unity or implement the arm shape using the RX-64.

Helper-code base for human posture recognition/classification

System for detection of abnormal or cheating activities in exam. This is done by using artificial neural networks for detecting the body posture of the student during the examination using the cctv footage of the classroom. Actions like turning back, bending etc are detected. Faces are registered to a database by pre-computing the face embeddings of the students.The student is recognised using facial recognition and a report about his activities along with a timestamp is sent to the examiners following which action can be taken after reviewing the report . Technologies involved are: machine learning for detection of student cheating activity in exam; OpenCV and deep learning for face recognition and identification. The database used is SQLite.

Human posture recognition,base on nanodet and movenet,ncnn

GitHub Desktop tutorial repository

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Human Activity Recognition(HAR) - Case Study : Wearable Computing: Accelerometers’ Data Classification of Body Postures and Movements, using Random forests classifier to quantify and predict best way to do exercise.