Kinect Sdk

  

Kinect for Windows SDK 2.0. Build desktop applications for Windows 10 or sell your Kinect v2 UWP apps in the Microsoft Store to take advantage of unique Windows Runtime features and expand distribution. GET THE KINECT FOR WINDOWS SDK. The Kinect SDK Sample Browser. This sample allows you to demonstrate that the video and infrared cameras are working properly. It also gives a very good demonstration of the body-tracking abilities of the Kinect system. The program is supplied as part of the SDK and will be copied onto your computer when you install the Kinect for Windows SDK. The Body Tracking SDK builds on the Azure Kinect SDK, using it to configure and connect to a device. Captured image data is processed by the tracker, storing data in a body frame data structure. Samurai warriors 2 1920x1080 screen pc. K inect VR is a Unity plugin that allows anyone with a mobile VR device and Microsoft Kinect to develop their own room scale VR experiences. Full-body position tracking data is sent over WiFi using a NodeJs server and then recieved on the mobile device to be used for avatar tracking in VR. Kinect for Windows SDK v1.8. Technical information about “Kinect for Windows SDK v1.8” available from MSDN Subscriber Downloads. Currently, you can find here information about 4 files. If you want to search for a specific file in the “Kinect for Windows SDK v1.8” section, enter the file name, MSDN code, SHA-1 hash, or any keyword from.

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Notice: MediaWiki has been updated. Report any rough edges to marcan@marcan.st

Welcome to the OpenKinect project

Language:Englishespañolsuomifrançaisitalianoportuguês do Brasil中文(简体)‎

About

OpenKinect is an open community of people interested in making use of the amazing Xbox Kinect hardware with our PCs and other devices. We are working on free, open source libraries that will enable the Kinect to be used with Windows, Linux, and Mac.

The OpenKinect community consists of over 2000 members contributing their time and code to the Project. Our members have joined this Project with the mission of creating the best possible suite of applications for the Kinect. OpenKinect is a true 'open source' community!

Our primary focus is currently the libfreenect software. Code contributed to OpenKinect where possible is made available under an Apache20 or optional GPL2 license.

  • Source code is available here: https://github.com/OpenKinect/libfreenect
  • Get started right away by installing the software to your platform.

Communications

If you want to participate or just watch the progress of the OpenKinect effort, subscribe to the OpenKinect mailing list. In the application form, please tell us something about yourself and you'll be approved automatically. You could also subscribe to the low-traffic announcement-only mailing list.

  • You can follow us on Twitter@openkinect. Please use the #tag #openkinect when tweeting your work.
  • You can meet people in your area working on OpenKinect through Meetup Groups:
  • You can also chat with people developing on OpenKinect software on IRC: #OpenKinect on irc.freenode.net or using this web based chat.
  • Channel logs (daily rotation) can be found here.

Project information

  • Project Roadmap - The current roadmap for the project (libfreenect, analysis library, and applications)
  • People - Who is doing what: project leader, maintainers, contributors etc.
  • Project History - The bounty, key dates and milestones
  • Project Policies - The official name of the project, license, contribution policy, developers coordination and decision making
  • Installation - How to download, build and install on Linux, OS X and Windows
  • Contributing Code - Official repositories, use of a fork and source header, signing off, submissions and evaluation etc.
  • Code Integration - How to deal with how we use git: repository policy, git usage, workflow, starting development, integration process etc.
  • Contributing - There are many ways to contribute: testing, administrative tasks, support related, documentation, collaboration etc.
  • FAQ - Frequently asked questions
  • Documentation - Documenation
  • Project Ideas - Ideas and concepts to explore using OpenKinect
  • Gallery and websites - Videos and links to things people are doing with OpenKinect
  • Official Logos - Official OpenKinect logos for use in your projects

Kinect Sdk Mac

API Documentation

  • High Level - High-level API documentation
  • Low Level - Low-level API documentation

Wrappers

  • C Synchronous - Provides functions to get data instead of callbacks
  • Common Lisp - Getting started with libfreenect on Common Lisp
  • GFreenect (GLib) - Use Freenect from GLib. Also provides GObject Introspection which means automatic bindings for many other languages (Python, Javascript, Vala)

Utilities

  • Record - Dumps Kinect data to PPM, PGM, and a bin dump for RGB, Depth, and Accel respectively.
  • Fakenect - libfreenect simulator/mock interface that lets you use the kinect demos without having a kinect (plays back data from Record)

Knowledge base

  • Protocol Documentation - Kinect USB procotol, structures and hardware control commands for the cameras, motor, LED and audio
  • Reference design - US Patent Application 'Depth mapping using projected patterns'
  • NUI Camera DSP - Camera DSP, architecture, instruction set, firmware, and capabilities
  • lsusb output - Device identifier output
  • USB Devices - Overview of the hardware devices
  • USB Protocol Information - Other information about the Kinect USB protocol
  • Init Analysis - Messing with various init sequences
  • Imaging Information - Information about the imaging data returned by the Kinect
  • Research Material - Research material for software layer implementation
  • Hardware_info - Hardware information
  • Calibration - Gathering information for including calibration facilities

Links

OpenNI

  • http://openni.org - Open Natural Interaction, an industry-led, not-for-profit organization formed to certify and promote the compatibility and interoperability of Natural Interaction (NI) devices, applications and middleware
  • http://github.com/openni - Open source framework for natural interaction devices
  • http://github.com/PrimeSense/Sensor - Open source driver for the PrimeSensor Development Kit

Tech

  • http://www.ifixit.com/Teardown/Microsoft-Kinect-Teardown/4066/ - Hardware teardown. Chip info is here. (via adafruit)
  • http://kinecthacks.net/kinect-pinout/ - Pinout info of the Kinect Sensor
  • http://www.primesense.com/?p=535 - Primesense reference implementation (via adafruit thread)
  • http://www.sensorland.com/HowPage090.html - How sensors work and the bayer filter
  • http://www.numenta.com/htm-overview/education/HTM_CorticalLearningAlgorithms.pdf - Suggestions to implement pseudocode near the end
  • http://www.dwheeler.com/essays/floss-license-slide.html - Which licenses are compatible with which
  • http://www.eetimes.com/design/signal-processing-dsp/4211071/Inside-Xbox-360-s-Kinect-controller - Another Hardware Teardown. Note this article incorrectly states that the PS1080 talks to the Marvell chip.
  • http://nvie.com/posts/a-successful-git-branching-model/ - Model for branching within Git
  • http://git.kernel.org/?p=linux/kernel/git/torvalds/linux-2.6.git;a=blob;f=Documentation/SubmittingPatches - Linux contribution procedure
  • http://git.kernel.org/?p=git/git.git;a=blob_plain;f=Documentation/SubmittingPatches;hb=HEAD - Git project contribution procedure
Retrieved from 'https://openkinect.org/w/index.php?title=Main_Page&oldid=1473'

by Andy Jeong, Yue Wang, Professor Mili Shah (Advisor)

Abstract

Body joint estimation from a single vision system poses limitations in the cases of occlusion and illumination changes, while current motion capture (MOCAP) systems may be expensive. This synchronized Azure Kinect-based MOCAP system serves as a remedy to both of these problems by creating a low-cost, portable, accurate body-tracking system.

Keywords: Motion capture (MOCAP) system, synchronization, Kinect, body-tracking

See Azure.com/Kinect for device info and available documentation.

Link to submitted poster to ACM SIGGRAPH’20: Poster

Link to submitted abstract to ACM SIGGRAPH’20: Abstract

(Received 4 feedback; 3 neutral, 1 slight negative)

Link to documentation: Documentation

Demo

Check out the outcomes on some various movements!Note: this demo experiences some offset due to a parallax problem (devices are at a lower height than the human).

Overview

Flowchart

Kinect Sdk Download

System Setup

Hardware

  • Ubuntu 18.04 / Windows PC machine with USB3.0+ support
  • USB Hub for multi-device connection (Targus 4-Port USB 3.0): Link
  • USB 3.0 Extension Cable for multi-device connection: Link
  • Audio Jack Cables for multi-device connection: Link

Software

  • Azure Kinect Senor SDK (K4A) (-lk4a)
  • Azure Kinect Body Tracking SDK (K4ABT) (-lk4abt)
  • OpenCV (`pkg-config --cflags --libs opencv`)

Building

Test Setup

Configuration

Kinect Sdk Windows 10

  • Daisy-chain configuration: supports connection of 2+ subordinate mode devices to a single master mode device (RS-232)

Testing Environment

Kinect Sdk

Camera Calibration to capture synchronous images

  • reference: green screen example from Azure Kinect SDK examples on its GitHub repository

Outcomes

With multiple devices in place, joint estimation is still performed as if there is no occlusion or lighting effect.The following videos and images are tested in the test setup shown above.

Videos Samples

2-Device3 -Device Systems
Kinect Sdk

Synchronization

  • on the right: joint angles for angles designated as below

Occlusion / Illumination Effect Verification with 3-Device System

Occlusion at Subordinate Device 0Occlusion at Subordinate Device 1Varying Illumination at Master Device

Example of selection of data streams by confidence levels per joint

Azure Kinect SDK Details

Azure Kinect SDK is a cross platform (Linux and Windows) user mode SDK to read data from your Azure Kinect device.

The Azure Kinect SDK enables you to get the most out of your Azure Kinect camera. Features include:

  • Depth camera access
  • RGB camera access and control (e.g. exposure and white balance)
  • Motion sensor (gyroscope and accelerometer) access
  • Synchronized Depth-RGB camera streaming with configurable delay between cameras
  • External device synchronization control with configurable delay offset between devices
  • Camera frame meta-data access for image resolution, timestamp and temperature
  • Device calibration data access

Current Work

1. Gait Analysis on Exoskeletons

Nitro pdf v9x core. OpenPose, AlphPose, Kinect, Vicon MOCAP system

Sdk
2. Graphical Visualization of Tracked Body Joints

Media art collaboration

3. Drone Movement Synchronzation from Human Pose

Control of drone system (crazyflie)