HANDY: A Configurable Gesture Recognition System
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Transcript of HANDY: A Configurable Gesture Recognition System
HANDY: A Configurable Gesture Recognition System
Mahsa Teimourikia1, Hassan Saidinejad2,,and Sara Comai3
Politecnico di Milano
[email protected], [email protected], [email protected] March 2014
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Motivations
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• To embed computer systems in the environments we need more natural ways of Human Computer Interactions
• Gesture-based interfaces are one of the natural ways that humans can use to interact with computers
• Gesture-based interfaces are still in an infant stage. And still not so natural!
• More fine grained gestures should be recognized
• Users should be able to define their preferred gestures
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Objectives
•Design and development of a gesture-based interface, adaptable to a specific user
•Recognition of the dynamic gestures based on the posture of the hand
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Methodology
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Hand Localization and Segmentation
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The environment setting:
Hand Localization and segmentation:
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Feature Extraction
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Skeletonization: Using Voronoi Diagrams on Boundary Points
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Hand Pose Estimation
• Resulted skeletons are not the same even in the same hand poses
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• Dynamic Time Warping (DTW) for pose estimation
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Gesture Recognition
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The Testing Application
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Results
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Average Recognition Accuracy
•Static Hand Pose Estimation : 83.53% •Gesture Recognition: 95.57%
• 7 persons, ages between 24 to 60, 5 right handed and 2 tested the system with the left hand.
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Conclusions
• This work has presented an approach for a flexible hand pose and gesture recognition system that can be adapted to the special needs of the users.
The interface:
• Is configurable for different hand poses
• Acceptable accuracy
• Can be trained with minimal effort to recognize user defined gestures and sequence of poses
• Can be used in uncontrolled environments, with dynamic background and low illumination. And the user does not need to use any wearable devices.
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Future Works
• As future work, hand pose estimator will be improved.
• Further extension of this system may include also facial expression recognition and vocal.
• This work can be used in several applications such as home automation.
• Since the proposed system is customizable it can be used for HCI purposes for people with different disabilities or needs.
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Thank You
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