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

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Presentation on theme: "Knowledge Systems Lab JN 1/15/2016 Facilitating User Interaction with Complex Systems via Hand Gesture Recognition MCIS Department Knowledge Systems Laboratory."— Presentation transcript:

1 Knowledge Systems Lab JN 1/15/2016 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

2 Knowledge Systems Lab JN 1/15/2016 Outline Motivation System Architecture Implementation Overview Proposed Approach Demonstration Future Directions

3 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

4 Knowledge Systems Lab JN 1/15/2016 Motivation (2) Interaction Problems with the Virtual Reality Glove –Reliability –Always connected –Encumbrance

5 Knowledge Systems Lab JN 1/15/2016 System Architecture Standard Web Camera Rendering User Interface Display Hand Movement User Gesture Recognition System Image Capture Update Object Image Input

6 Knowledge Systems Lab JN 1/15/2016 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

7 Knowledge Systems Lab JN 1/15/2016 Implementation Overview (2) Hand Calibration Measure: Max hand size in x and y orientations in # of pixels

8 Knowledge Systems Lab JN 1/15/2016 Implementation Overview (3) Saturation Channel Extraction (HSL space): Original Image Hue Lightness Saturation

9 Knowledge Systems Lab JN 1/15/2016 Proposed Approach

10 Knowledge Systems Lab JN 1/15/2016 Proposed Approach (2)

11 Knowledge Systems Lab JN 1/15/2016 Proposed Approach (3) 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

12 Knowledge Systems Lab JN 1/15/2016 Proposed Approach (4) System Runtime: Current time – 41 ms for one image from camera Processing Capability on 1.6 Ghz Athlon: 24 fps Process Steps Time (ms) Athlon XP 1900 (1.6 Ghz) 1) Extract Sat Channel9 2) Threshold3 3) Connected Contour Fill 14 4) Centroid2 5) Segment Hand From Arm 9 6) Refined Centroid4 7) Count Number of Fingers 0 Total Time41

13 Knowledge Systems Lab JN 1/15/2016 Demonstration System Configuration System GUI Layout

14 Knowledge Systems Lab JN 1/15/2016 Demonstration (2) Gesture to Interaction Mapping Number of Fingers: 2 – Roll Left 3 – Roll Right 4 – Zoom In 5 – Zoom Out

15 Knowledge Systems Lab JN 1/15/2016 Demonstration (3)

16 Knowledge Systems Lab JN 1/15/2016 Demonstration (4)

17 Knowledge Systems Lab JN 1/15/2016 Future Directions Optimization Calibration Phase Defining Hand Orientation Learning System Interface Extensions For additional information, please visit http://ksl.jsu.edu.


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