01-05-2013, 04:21 PM
Contactless Gesture Recognition System Using Proximity Sensors
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ABSTRACT
In this paper, we present a novel contactless gesture recognition system using proximity sensors. A set of infrared signal feature extraction methods and a decision-tree-based gesture classifier are proposed. The system allows a user to interact with mobile devices using intuitive gestures, without touching the screen or wearing/holding any additional device. Evaluation results show that the system is low power, and able to recognize 3D gestures with over 98% precisions in real time.
INTRODUCTION
Gesture-based interfaces provide an intuitive way for users to specify commands and interact with computers. Existing gesture recognition systems can be classified into three types: motion-based, touch-based, and vision-based systems. While the first two types of system require users to make contact with devices, vision-based systems are computationally expensive and power consuming, which are undesirable for resource-limited mobile devices like tablets or mobile phones. To solve the existing challenges, we present a novel gesture recognition system with the following contributions:
• The design and evaluation of the first contactless gesture recognition system using only infrared proximity sensors.
• The proposed infrared (IR) feature set and classifier for real-time 3D gesture classification.
• Reducing the power consumption of gesture recognition.
• The design also reduces the frequency of users’ contact with devices, alleviating the wear and tear of screen surface.
Proximity Sensor Data Acquisition Method
For the configuration under study, a proximity sensor consists of two IR LEDs and a IR receiver, which are placed underneath a plastic/glass screen surface, surrounded by optical barriers. The LEDs emit IR strobes in turns as two separate channels. When a hand or any object is near, the receiver detects the reflection of the IR light, whose intensity increases as the object distance decreases.