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3D Indoor Positioning System Midterm Presentation SD May 11-17. Faculty Advisor: Dr. Daji Qiao. Members: Nicholas Allendorf - CprE Christopher Daly – CprE Daniel Guilliams – CprE Andrew Joseph – EE Adam Schuster – CprE. Client: Dr. Stephen Gilbert Virtual Reality Application Center. - PowerPoint PPT Presentation
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3D Indoor Positioning SystemMidterm PresentationSD May 11-17
Members:Nicholas Allendorf - CprE
Christopher Daly – CprEDaniel Guilliams – CprE
Andrew Joseph – EEAdam Schuster – CprE
Faculty Advisor:Dr. Daji Qiao
Client: Dr. Stephen GilbertVirtual Reality Application Center
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• Create a system capable of accurately tracking fingertips in three dimensions
• Incorporate the ability to support as many as six users simultaneously
• Design the system so that it is easily reproducible
Big Picture Goals
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Project Requirements• Provide a 3D position of all tracked fingertips
within a 2m x 2m x 2m indoor region with 1 centimeter accuracy
• Update positions 15 times per second (15 Hz) with low latency
• The system shall be capable of tracking as many as 60 fingertip positions simultaneously
• Positions shall be displayed in a graphical interface so the position may be viewed in real time
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Project Plan• Use Optical/Infrared tracking
– Most practical solution and cost effective solution
• Use stereo cameras to track and localize IR LEDs embedded on gloves
• Process images with a desktop computer and open source computer vision software
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System Design and Layout• Glove
– Contains IR LEDs/color markers on fingertips which will be tracked by the cameras
• Infrastructure– Provides stable and measurable mounting points for the
cameras• Cameras
– Mounted in stereo pairs around periphery of infrastructure– Detect IR LEDs and pass images to server for processing
• Server/Computer– Performs image processing, calculates position, and runs
the GUI
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System Hardware/Software• Cameras : Logitech QuickCam Pro 9000• Computer : Dell XPS• LEDs : 950 nm Surface Mount Infrared LEDs• Infrastructure : 8020 Aluminum Framing
• Operating System: Windows 7• Image Processing: OpenCV
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Preliminary Results• Gloves
– A seamstress is working on making a glove of our design– Battery Pack consists of 4 AAA batteries to give ~20 hrs of continuous use
• Stereo Cameras– The first stereo camera is assembled and working well– Another set of cameras arrived just this week – assembly imminent
• IR Filter– The developed film filters worked ok, but image quality was an issue– Changed to a low cost commercial Longpass IR Filters, which is much more
effective than than the old developed film
• Infrastructure– Rudimentary infrastructure in place, but more parts are needed
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IR LED with new filter on camera IR LED with old filter on camera
Preliminary Results
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Assembled stereo camera with filters Infrastructure around TV
Preliminary Results
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Preliminary Results• Camera Calibration
– Using a checkerboard pattern and OpenCV to rectify images– Initially, Calibration was inaccurate and unusable– Calibration has improved, and our average error values are now in an
acceptable range
• Image Processing and Finger Identification– Currently able to easily identify locations of IR LEDs in filtered images– Initially we were unsure of how to discriminate between fingers– New solution: One camera with a filter, and one without, and colored
fingertips on the glove to discriminate between fingers
• Localization/Tracking– With an accurate calibration and good LED location we are able to
produce a 3D location of a single LED– Nearly able to do so for multiple LEDs– Localization needs to be improved – Good precision, poor accuracy
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Current Schedule
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Questions?
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Thanks for your time!