DocumentCode :
1642530
Title :
Kinect based real-time gesture spotting using HCRF
Author :
Chikkanna, Mahesh ; Guddeti, Ram Mohana Reddy
Author_Institution :
Nat. Inst. of Technol. Karnataka, Mangalore, India
fYear :
2013
Firstpage :
925
Lastpage :
928
Abstract :
The sign language is an effective way of communication for deaf and dumb people. This paper proposes, developing the gesture spotting algorithm for Indian Sign Language that acquires sensory information from Microsoft Kinect Sensor. Our framework consists of three main stages: hand tracking, feature extraction and classification. In the first stage, hand tracking is carried out using frames of Kinect. In second stage, the features of Cartesian system (velocity, angle, location) and hand with respect to body are extracted. K-means is used for extracting the codewords of features for HCRF. In the third stage, Hidden Conditional Random Field is used for classification. The experimental results show that HCRF algorithm gives 95.20% recognition rate for the test data. In real-time, the recognition rate achieves 93.20% recognition rate.
Keywords :
feature extraction; image classification; medical disorders; object detection; object tracking; random processes; sign language recognition; Cartesian system; HCRF; Indian Sign Language; K-means; Kinect based real-time gesture spotting; Microsoft Kinect Sensor; classification; deaf-and-dumb people; feature codeword extraction; feature extraction; gesture spotting algorithm; hand angle; hand location; hand tracking; hand velocity; hidden conditional random field; recognition rate; sensory information; sign language; Assistive technology; Conferences; Equations; Feature extraction; Gesture recognition; Hidden Markov models; Real-time systems; Gesture Spotting; Hidden Conditional Random Field; Indian Sign Language; Kinect;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4799-2432-5
Type :
conf
DOI :
10.1109/ICACCI.2013.6637300
Filename :
6637300
Link To Document :
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