A simple software for capturing human body movements using the Kinect camera.

Overview

KinectMotionCapture

Build Status DOI

A simple software for capturing human body movements using the Kinect camera. The software can seamlessly save joints and bones positions for further analysis.

Features

  • Compliance with one Kinect camera connected.
  • Tracking up to two people captured on the video stream.
  • Indicating by color which joints and bones are fully tracked or inferred.
  • Recording body movements of one person. Bones and joints positions data is saved to files.
  • Adjusting joint filtering options.
  • Saving screenshots of current video stream.

The application recognizes only joints and bones that were fully tracked or inferred by the Kinect camera. Tracked joints and bones with both of their joints tracked are indicated by green color, inferred joints and bones with only one of their joints tracked are indicated by yellow color, and bones with both of their joint inferred are indicated by red color.

Although being capable of tracking up to two skeletons on the video stream, the application saves all positions as if there was only one skeleton source. Therefore, if more than one skeleton is tracked, the user should indicate the main body to be captured by using the Set body function.

For a general overview of the Kinect skeletal tracking system please refer to [1].

Functions

Set body

The Set body function allows to choose the body to be captured (and its position saved) from all other bodies present on the video stream. To use this feature, the person to be captured must stand the closest to the camera, and then the Set body button must be clicked.

Kinect smoothing parameters

The skeletal tracking joint information can be adjusted across different frames to minimize jittering and stabilize the joint positions over time. This can be done by adjusting the smoothing parameters. A comprehensive description of these options can be found at [1].

Recording

Body movement can be recorded by clicking the Start recoding button. All data recorded is saved as comma-separated files in “data” folder in the root directory of the application. For the data file to be saved the Stop recording button must be clicked afterwards. Joints positions are saved as files named “<>-joint-<>.csv”. The files include data columns which contain timestamp of a measurement (timestamp), joint x position (x), joint y position (y), joint z position (z), and coordinate type (coord_type), which indicates whether the joint was fully tracked (1) or inferred (2). Bones positions are saved as files named “<>-bone-<>-<>.csv”. The files include data columns which contain timestamp of a measurement (timestamp), bone absolute rotation matrix (abs_m11 to abs_m44), bone absolute orientation in quaternion form (abs_x, abs_y, abs_z, and abs_w), bone hierarchical rotation matrix (h_m11 to h_m44), bone hierarchical orientation in quaternion form (h_x, h_y, h_z, and h_w), and coordinate type (coord_type), which indicates whether both joints of the bone were fully tracked (1), both were inferred (2) or only one of them was tracked (3).

Requirements

  • .NET Framework 4.5.2
  • Kinect for Windows SDK v1.8

References

[1] https://msdn.microsoft.com/en-us/library/hh973074.aspx

You might also like...
 SMPL-X: A new joint 3D model of the human body, face and hands together
SMPL-X: A new joint 3D model of the human body, face and hands together

SMPL-X: A new joint 3D model of the human body, face and hands together [Paper Page] [Paper] [Supp. Mat.] Table of Contents License Description News I

Face and Pose detector that emits MQTT events when a face or human body is detected and not detected.
Face and Pose detector that emits MQTT events when a face or human body is detected and not detected.

Face Detect MQTT Face or Pose detector that emits MQTT events when a face or human body is detected and not detected. I built this as an alternative t

Camera-caps - Examine the camera capabilities for V4l2 cameras
Camera-caps - Examine the camera capabilities for V4l2 cameras

camera-caps This is a graphical user interface over the v4l2-ctl command line to

 PoseViz – Multi-person, multi-camera 3D human pose visualization tool built using Mayavi.
PoseViz – Multi-person, multi-camera 3D human pose visualization tool built using Mayavi.

PoseViz – 3D Human Pose Visualizer Multi-person, multi-camera 3D human pose visualization tool built using Mayavi. As used in MeTRAbs visualizations.

CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images
CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images

CFC-Net This project hosts the official implementation for the paper: CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Dete

Towards Multi-Camera 3D Human Pose Estimation in Wild Environment
Towards Multi-Camera 3D Human Pose Estimation in Wild Environment

PanopticStudio Toolbox This repository has a toolbox to download, process, and visualize the Panoptic Studio (Panoptic) data. Note: Sep-21-2020: Curre

Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.
Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.

Python scripts for performing 3D human pose estimation using the Mobile Human Pose model in ONNX.

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp

[CVPR2021] UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles

UAV-Human Official repository for CVPR2021: UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicle Paper arXiv Res

Releases(v1.1)
Owner
Aleksander Palkowski
Aleksander Palkowski
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption

⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

Lukas Hedegaard 21 Dec 22, 2022
Official PyTorch implementation of "Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics".

Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics This repository is the official PyTorch implementation of "Physics-aware Differ

USC-Melady 46 Nov 20, 2022
Adds timm pretrained backbone to pytorch's FasterRcnn model

Operating Systems Lab (ETCS-352) Experiments for Operating Systems Lab (ETCS-352) performed by me in 2021 at uni. All codes are written by me except t

Mriganka Nath 12 Dec 03, 2022
A lightweight library to compare different PyTorch implementations of the same network architecture.

TorchBug is a lightweight library designed to compare two PyTorch implementations of the same network architecture. It allows you to count, and compar

Arjun Krishnakumar 5 Jan 02, 2023
Platform-agnostic AI Framework 🔥

🇬🇧 TensorLayerX is a multi-backend AI framework, which can run on almost all operation systems and AI hardwares, and support hybrid-framework progra

TensorLayer Community 171 Jan 06, 2023
Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces

This repository contains source code for the paper Combining Latent Space and Structured Kernels for Bayesian Optimization over Combinatorial Spaces a

9 Nov 21, 2022
This is the official code for the paper "Ad2Attack: Adaptive Adversarial Attack for Real-Time UAV Tracking".

Ad^2Attack:Adaptive Adversarial Attack on Real-Time UAV Tracking Demo video 📹 Our video on bilibili demonstrates the test results of Ad^2Attack on se

Intelligent Vision for Robotics in Complex Environment 10 Nov 07, 2022
A TensorFlow implementation of SOFA, the Simulator for OFfline LeArning and evaluation.

SOFA This repository is the implementation of SOFA, the Simulator for OFfline leArning and evaluation. Keeping Dataset Biases out of the Simulation: A

22 Nov 23, 2022
Reinforcement Learning via Supervised Learning

Reinforcement Learning via Supervised Learning Installation Run pip install -e . in an environment with Python = 3.7.0, 3.9. The code depends on MuJ

Scott Emmons 49 Nov 28, 2022
Official Implementation (PyTorch) of "Point Cloud Augmentation with Weighted Local Transformations", ICCV 2021

PointWOLF: Point Cloud Augmentation with Weighted Local Transformations This repository is the implementation of PointWOLF(To appear). Sihyeon Kim1*,

MLV Lab (Machine Learning and Vision Lab at Korea University) 16 Nov 03, 2022
Infrastructure as Code (IaC) for a self-hosted version of Gnosis Safe on AWS

Welcome to Yearn Gnosis Safe! Setting up your local environment Infrastructure Deploying Gnosis Safe Prerequisites 1. Create infrastructure for secret

Numan 16 Jul 18, 2022
Examples of how to create colorful, annotated equations in Latex using Tikz.

The file "eqn_annotate.tex" is the main latex file. This repository provides four examples of annotated equations: [example_prob.tex] A simple one ins

SyNeRCyS Research Lab 3.2k Jan 05, 2023
PyTorch implementation of the end-to-end coreference resolution model with different higher-order inference methods.

End-to-End Coreference Resolution with Different Higher-Order Inference Methods This repository contains the implementation of the paper: Revealing th

Liyan 52 Jan 04, 2023
Cookiecutter PyTorch Lightning

Cookiecutter PyTorch Lightning Instructions # install cookiecutter pip install cookiecutter

Mazen 8 Nov 06, 2022
Neural Koopman Lyapunov Control

Neural-Koopman-Lyapunov-Control Code for our paper: Neural Koopman Lyapunov Control Requirements dReal4: v4.19.02.1 PyTorch: 1.2.0 The learning framew

Vrushabh Zinage 6 Dec 24, 2022
simple artificial intelligence utilities

Simple AI Project home: http://github.com/simpleai-team/simpleai This lib implements many of the artificial intelligence algorithms described on the b

921 Dec 08, 2022
Rayvens makes it possible for data scientists to access hundreds of data services within Ray with little effort.

Rayvens augments Ray with events. With Rayvens, Ray applications can subscribe to event streams, process and produce events. Rayvens leverages Apache

CodeFlare 32 Dec 25, 2022
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki

DeepCourse: Deep Learning for Computer Vision arthurdouillard.com/deepcourse/ This is a course I'm giving to the French engineering school EPITA each

Arthur Douillard 113 Nov 29, 2022
SpanNER: Named EntityRe-/Recognition as Span Prediction

SpanNER: Named EntityRe-/Recognition as Span Prediction Overview | Demo | Installation | Preprocessing | Prepare Models | Running | System Combination

NeuLab 104 Dec 17, 2022
Implementation of gaze tracking and demo

Predicting Customer Demand by Using Gaze Detecting and Object Tracking This project is the integration of gaze detecting and object tracking. Predict

2 Oct 20, 2022