Knowledge Systems Lab JN 1/15/2016 Facilitating User Interaction with Complex Systems via Hand...

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JN 07/05/22 Knowledge Systems Lab Facilitating User Interaction with Complex Systems via Hand Gesture Recognition MCIS Department Knowledge Systems Laboratory Jacksonville State University Joshua R. New, Erion Hasanbelliu, and Mario Aguilar

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Knowledge Systems Lab JN 1/15/2016 Motivation Gesturing is a natural form of communication Interaction problems with the mouse –Have to locate cursor –Hard for some to control (Parkinsons or people on a train) –Limited forms of input from the mouse

Transcript of Knowledge Systems Lab JN 1/15/2016 Facilitating User Interaction with Complex Systems via Hand...

Page 1: Knowledge Systems Lab JN 1/15/2016 Facilitating User Interaction with Complex Systems via Hand Gesture Recognition MCIS Department Knowledge Systems Laboratory.

JN 05/03/23 Knowledge Systems Lab

Facilitating User Interaction with Complex Systems via

Hand Gesture Recognition

MCIS DepartmentKnowledge Systems Laboratory

Jacksonville State University

Joshua R. New, Erion Hasanbelliu, andMario Aguilar

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Outline

• Motivation• System Architecture• Implementation Overview• Proposed Approach• Demonstration• Future Directions

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Motivation

• Gesturing is a natural form of communication

• Interaction problems with the mouse– Have to locate cursor– Hard for some to control (Parkinsons or

people on a train)– Limited forms of input from the mouse

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Motivation (2)

• Interaction Problems with the Virtual Reality Glove– Reliability– Always connected – Encumbrance

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System Architecture

StandardWeb Camera

Rendering

User InterfaceDisplay

Hand

M

ovem

ent

User

Gesture Recognition

System

ImageCapture

Update Object

Image Input

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Implementation Overview• System:

• 1.6 Ghz AMD Athlon• OpenCV and IPL libraries (from Intel)

• Input:• 640x480 video image• Hand calibration measure

• Output:• Rough estimate of centroid• Refined estimate of centroid• Number of fingers being held up• Manipulation of 3D skull in QT interface in response to

gesturing

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Implementation Overview (2)• Hand Calibration Measure:

• Max hand size in x and y orientations in # of pixels

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Implementation Overview (3)

Saturation Channel Extraction (HSL space):

Original ImageOriginal Image Hue

Lightness

Saturation

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Proposed Approach

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Proposed Approach (2)

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Proposed Approach (3)

)(*19.0 HandSizeYHandSizeXRadius

• The finger-finding function sweeps out a circle around the rCoM, counting the number of white and black pixels as it progresses

• A finger is defined to be any 10+ white pixels separated by 17+ black pixels (salt/pepper tolerance)

• Total fingers is number of fingers minus 1 for the hand itself

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Proposed Approach (4)

System Runtime:

• Current time – 41 ms for one image from camera

• Processing Capability on 1.6 Ghz Athlon:• 24 fps

ProcessSteps

Time (ms)Athlon

XP 1900(1.6 Ghz)

1) Extract Sat Channel 9

2) Threshold 3

3) Connected Contour Fill

14

4) Centroid 2

5) Segment Hand From Arm

9

6) Refined Centroid 4

7) Count Number of Fingers

0

Total Time 41

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Demonstration

SystemConfiguration

SystemGUI Layout

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Demonstration (2)Gesture to Interaction Mapping

Number of Fingers:

2 – Roll Left3 – Roll Right

4 – Zoom In5 – Zoom Out

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Demonstration (3)

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Demonstration (4)

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Future Directions

• Optimization• Calibration Phase• Defining Hand Orientation• Learning System• Interface Extensions

For additional information, please visit http://ksl.jsu.edu.