Kinect
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Kinect

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Kinect Kinect Presentation Transcript

  • KINECT MOTION TECHNOLOGY
  • CONTENTS INTRODUCTION LITERATURE SURVEY CONCEPTS REAL TIME CASE STUDIES APPLICATIONS COMPARISONS ADVANTAGES AND DISADVANTAGES RESULT ANALYSIS CONCLUSIONS REFERENCES
  • INTRODUCTION Kinect motion technology uses a sensor device called kinect,a 3D scanner which interprets 3D scene information from a continuously projected infrared structured light. Is used for: –Xbox 360 console –Windows PCs –Robots
  • Contd Kinect was developed by microsoft . Enables users to control and interact with the application/game. –Without the need to touch a game controller . –Through a natural user interface . –Using gestures and spoken commands .
  • What is NUI ? Natural User Interface:  An Invisible Interface Direct Manipulation  Gestural interfaces
  • LITERATURE SURVEY  PAPER 1 Skeleton Tracking using Kinect Sensor &Displaying in 3D Virtual Scene -ChanjiraSinthanayothin, Nonlapas Wongwaen, Wisarut Bholsithi. (IJACT-2012).
  • PAPER 2 Motion Detection Real Time 3D Walkthrough in Limkokwing University of Creative Technology (Modet-Walk) using Kinect XBox -Behrang Parhizkari,Kanammal Sandrasekaran and Arash Habibi Lashkari(IJCSI-2012).
  • KINECT SYSTEM Consists of: 3D Depth sensor  RGB camera Motorized tilt Multi-array microphones
  • KINECT SENSOR
  •  3-D depth sensors Three-dimensional sensors tracks the body within the play space.  RGB camera An RGB (640 × 480) pixels helps identify and takes in-game pictures and videos. Multiple microphones An array of microphones along the bottom, front edge of the Kinect sensor are used for speech recognition and chat. Motorized tilt A mechanical drive in the base of the Kinect sensor
  • PrimeSense 3D sensing technology
  • Kinect Features Full-body 3D motion capture Gesture recognition Facial recognition Voice recognition capabilities
  • Light Coding With Kinect: Structured light is a form of active triangulation. In structured light,a known pattern is projected onto the scene, and the depth is calculated on the basis of the triangulation between a known reference pattern and observed reflected pattern.
  • Working: Depth perception using the infrared camera
  • Methodology
  • Detected face and upper body regions in the RGB image
  • Software: The poses of human skeleton is recognized with the help of machine learning algorithm called decision tree . Construction of skeleton image
  • CASE STUDY The TurtleBot is a customizable mobile robotic platform that rides on an iRobot Create platform . The TurtleBot uses the Kinect to see the world in 3D and for detecting and tracking people.
  • APPLICATIONS Health Care Virtual Piano DepthJS
  • COMPARISIONS: Topic NUI GUI Ease User can learn features easily through natural movements New users may have a difficult time learning to use the mouse and all GUI features. Speed Depends on the user User must operate using mouse and keyboard Strain No strain Shortcut keys are used Example 3D immersive touch Gnome shell
  • ADVANTAGES No Data Input Device Required Voice Recognition Facial Recognition Portable
  • DISADVANTAGES Sensitive to external infrared source (sunlight). Cannot detect crystalline or highly reflective objects.
  • RESULT ANALYSIS Detection and tracking of one or two people moving in the field of view of the sensor, using the tracking of parts of the skeleton. Capture audio with noise and echo cancellation. Speech Recognition.
  • CONCLUSION This technique aims to provide an application that uses gestures to interact with virtual objects in an Augmented Reality application.  Providing a way for using the gesture-based interactions to manage operations in a virtual walkthrough environment is a promising approach.
  • REFERENCES [1] http://www.wired.com/wiredscience/hacked- kinect-science/ [2] http://en.wikipedia.org/wiki/Kinect [3] http://electronics.howstuffworks.com/microsoft- kinect.html [4] http://www.microsoft.com/en- us/kinectforwindows/
  • THANK YOU
  • QUERIES?