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Craig Newman Curtin University of Technology Translating Australian Sign Language into Speech
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Introduction To Auslan Elements Of Auslan Signs Hardware Used Hardware Control Algorithm Elements Of Sign Recognition Algorithm Future Intentions Presentation Overview
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British and Irish origins More than 4000 commonly used signs 0.1% of Australians use Auslan Introduction to Auslan
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Two-handed fingerspelling alphabet
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Handshapes Location Orientation Movement Expression Elements of Auslan signs
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Handshapes
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First Attribute: Degree to which fingers are bent
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Handshapes Second Attribute: Combination of fingers touching
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Handshapes Third Attribute: Pitch of the hand
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Neutral Space Primary Locations Secondary Locations Location
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Orientation
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Roll required to differentiate Yaw required to differentiate
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Large Scale Straight Line Series of Straight Lines Arcs Circles Small Scale Changes in Orientation Changes in Fingers New Handshape Movement
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Head Eyebrows Eyes Mouth Cheeks Expression
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P5 glove from Essential Reality
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Known through the P5 Degree of Finger Bend Position Primary Locations, Movement Orientation Required Contacting Secondary Locations What was Needed?
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Acquiring Secondary Locations
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M16C/62 Single-chip Microcontroller
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The Prototype
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Collect Data Every 17ms 60 Hertz Synchronisation with P5 Test Pins Not Logged Write Pin High, Read Remaining Pins Log Connected Pins Debounce: Test For Consistency Encapsulate for Transmission Transmit When Required Contact Sensor Algorithm
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Working Example 1
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Working Example 2 INSERT CLIP: IM
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3 Samples Stored in stop_buffer Position Orientation Finger Bend Contacts Check Last 2 Samples within Range When was the hand considered Stopped?
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Wait Until Hands Stop Take First Sample From stop_buffer Filter Through if/else Structure to find Correct Combination Return Handshape Identifying Handshapes
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Working Example 1 INSERT CLIP: GUN
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Working Example 2 INSERT CLIP: MOTHER
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Record Position of Head Shoulder Bicep Forearm Extrapolate Primary Locations Else is Neutral Space Problem Requires Dynamic Position Tracking Identifying Primary Locations
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Wait Until “not stopped” While “not stopped” copy stop_buffer Allow for Slight Pauses Filter Data By Testing For Inherent Geometric Structure Output Movement Type Identifying Movement Type
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Identify Initial Handshape, Location, Orientation Filter Through if/else Structure If Sign Recognised Output Sign Else Identify Movement Identify Final Handshape, Location, Orientation Filter through if/else Structure Output Sign Putting it all together: Recognizing Signs
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Working Example INSERT CLIP: WRAPUP2
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Design Composite Glove Dynamic Tracking Of Primary Locations Introduce Learning Algorithms Identifying Handshapes Identifying Movement Translate Signing Context Into English Text Integrate Text To Voice Synthesizer Future Intentions
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Questions & Answers
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