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

1mahsa.teimourikia@polimi.it, 2hassan.saidinejad@polimi.it, 3sara.comai@polimi.it 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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