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Ari Y' Benbasat

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Compact. Inertial Measurement Unit. Full sensor set for 3D motion detection in compact wireless ... Compact / low-poweruseable in a wide variety of situations ... – PowerPoint PPT presentation

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Title: Ari Y' Benbasat


1
Inertial Gesture Recognition
  • Ari Y. Benbasat
  • Responsive Environments Group
  • MIT Media Laboratory

2
Compact Inertial Measurement Unit
  • Full sensor set for 3D motion detection in
    compact wireless package.
  • Implementation
  • 3(1) Accelerometers
  • 3 Gyroscopes
  • 12-bit ADC/Microcontroller
  • 900 MHz wireless link
  • Low-power (75mW)

3
S.M. Thesis Work
Project Organization
  • Create analysis and interpretation framework for
    such devices
  • Analysis Activity detection
  • Gesture Recognition Parameterized atomic
    gestures
  • Output Scripting Links gestures to outputs
  • Applications
  • Current Re-implementation of (void)
  • Future Gesture-based control and learning

4
Activity Detection
  • Simple scheme based on windowed variance
  • Piecewise model of model used to analytically
    find threshold
  • Finds areas of interest in data streams to be
    analyzed by the gesture recognition system
  • Err on side of false positives
  • Stuttering gestures OK

5
Gesture Recognition
  • Parameterized
  • Magnitude and duration are properties of the
    detected gestures, not fundamental to the process
  • Atomic
  • Considered on axis at a time
  • Considered only in units of a number of peaks
  • Algorithm
  • Expects net zero sum (accelerometers)
  • Non-trivial size (gyroscopes)
  • Pieces together stuttering gestures by combining
    failed gestures
  • Breaks gestures if polarity of adjacent peaks is
    identical

6
Output / Applications
  • Simple JPython script allows temporal and logical
    combinations of gestures to be linked to output
    routines
  • Value in Applications
  • Allows direct, in situ sensing of quantities of
    interest
  • Compact / low-power?useable in a wide variety of
    situations
  • Low complexity of algorithms allows for
    stand-alone devices ? combined perception and
    expertise in single device
  • Not limited to human gesture

7
Sample Analysis
Find Areas of Activity
Perform Gestures and Collect Data
y
x
(no rotation)
Run Recognition
Recombine Atomic Output
2 Peaks




3 Peaks
8
Sample Analysis (2)
  • Perform gesture
  • Sweeping twist
  • Find gestures in stream
  • One axis at a time
  • Note baseline subtraction
  • Recombine atoms
  • Can be tied to output

1 Peak (gyro)


2 Peaks (acc)
sound light etc.

causes
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