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!