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OpenPose is a real-time pose estimation engine designed to detect and track human body, face, hand, and foot landmarks. It functions as a multi-person motion tracker, identifying the spatial coordinates of multiple individuals simultaneously within video streams or static images. Beyond two-dimensional detection, the software acts as a three-dimensional kinematics processor, reconstructing spatial movement data from single or multiple synchronized camera perspectives. The system distinguishes itself through a bottom-up approach that utilizes part-affinity fields to associate body parts across
This project is a deep learning framework built for detecting and tracking human body keypoints in images and video streams. It functions as both a real-time motion tracking system and a machine learning environment for training and evaluating pose estimation models. The system utilizes a two-branch convolutional neural network to predict body part locations and their directional connections simultaneously. It employs multi-stage feature refinement to improve keypoint localization accuracy and uses greedy parsing and bipartite matching algorithms to associate detected parts into individual sk
AlphaPose is a deep learning pose estimation framework and PyTorch computer vision library designed for detecting and tracking human body, face, hand, and foot keypoints in images and videos. It provides a system for skeletal posture estimation and multi-person pose tracking. The project implements tools for three-dimensional human pose reconstruction, generating joint positions and body mesh shapes from two-dimensional image data. It also includes a multi-person pose tracker capable of maintaining the identity of multiple people across consecutive video frames. The framework covers a broad
This project is a Java-based toolkit that integrates the OpenCV computer vision library into the Processing creative coding environment. It provides a programming interface designed to facilitate the inclusion of real-time image analysis and computer vision algorithms within interactive art installations and visual design projects. The library distinguishes itself by wrapping low-level C++ routines into a managed environment, allowing users to perform complex visual tasks through a simplified interface. It supports high-performance operations by sharing raw pixel data between the host environ
FreeMoCap is an open-source markerless motion capture system that reconstructs 3D human pose from video. It uses a multi-camera setup with ChArUco board calibration to accurately triangulate body landmarks, and it also supports single-camera recording for simpler captures. The system outputs skeleton joint data and generates interactive Jupyter notebooks for each recording, enabling users to explore and analyse motion data directly.
The main features of freemocap/freemocap are: Motion Capture, 3D Pose Reconstruction, Camera Calibration, Multi-View Geometry Solvers, Open Source Toolkits, Project-Specific Notebooks, Calibrated Multi-Camera Recordings, Video-Based Reconstructions.
Open-source alternatives to freemocap/freemocap include: cmu-perceptual-computing-lab/openpose — OpenPose is a real-time pose estimation engine designed to detect and track human body, face, hand, and foot… tensorboy/pytorch_realtime_multi-person_pose_estimation — This project is a deep learning framework built for detecting and tracking human body keypoints in images and video… mvig-sjtu/alphapose — AlphaPose is a deep learning pose estimation framework and PyTorch computer vision library designed for detecting and… atduskgreg/opencv-processing — This project is a Java-based toolkit that integrates the OpenCV computer vision library into the Processing creative… gyroflow/gyroflow — Gyroflow is a gyroscope video stabilization software and IMU telemetry processor designed to remove camera shake from… nvidia/isaac-gr00t.