Paper Info
Title
Kinect Based Real-Time Gesture Spotting Using Hcrf
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.
Year
Venue
Keywords
2013
2013 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI)
Hidden Conditional Random Field, Kinect, Gesture Spotting, Indian Sign Language
Field
DocType
Citations 
Conditional random field,Computer vision,Object detection,Computer science,Gesture recognition,Feature extraction,Video tracking,Sign language,Artificial intelligence,Test data,Contextual image classification
Conference
2
PageRank 
References 
Authors
0.40
11
2
Name
Order
Citations
PageRank
Mahesh Chikkanna120.40
Ram Mohana Reddy Guddeti2488.76