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Real Time Skeleton Tracking based Human Recognition System using Kinect and Arduino

Published on May 2015 by Satish Prabhu, Jay Kumar Bhuchhada, Amankumar Dabhi, Pratik Shetty
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National Conference on Role of Engineers in Nation Building
Foundation of Computer Science USA
NCRENB2015 - Number 2
May 2015
Authors: Satish Prabhu, Jay Kumar Bhuchhada, Amankumar Dabhi, Pratik Shetty
95732960-318d-4fa9-b64d-5937bf2a89d6

Satish Prabhu, Jay Kumar Bhuchhada, Amankumar Dabhi, Pratik Shetty . Real Time Skeleton Tracking based Human Recognition System using Kinect and Arduino. National Conference on Role of Engineers in Nation Building. NCRENB2015, 2 (May 2015), 1-6.

@article{
author = { Satish Prabhu, Jay Kumar Bhuchhada, Amankumar Dabhi, Pratik Shetty },
title = { Real Time Skeleton Tracking based Human Recognition System using Kinect and Arduino },
journal = { National Conference on Role of Engineers in Nation Building },
issue_date = { May 2015 },
volume = { NCRENB2015 },
number = { 2 },
month = { May },
year = { 2015 },
issn = 0975-8887,
pages = { 1-6 },
numpages = 6,
url = { /proceedings/ncrenb2015/number2/20971-7023/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Role of Engineers in Nation Building
%A Satish Prabhu
%A Jay Kumar Bhuchhada
%A Amankumar Dabhi
%A Pratik Shetty
%T Real Time Skeleton Tracking based Human Recognition System using Kinect and Arduino
%J National Conference on Role of Engineers in Nation Building
%@ 0975-8887
%V NCRENB2015
%N 2
%P 1-6
%D 2015
%I International Journal of Computer Applications
Abstract

A Microsoft Kinect sensor has high resolution depth and RGB/depth sensing which is becoming available for wide spread use. It consists of object tracking, object detection and reorganization. It also recognizes human activity analysis, hand gesture analysis and 3D mapping. Face expression detection is widely used in computer human interface. Kinect depth camera can be used for detection of common face expressions. Face is tracked using MS Kinect which uses 2. 0 SDK. This makes use of depth map to create a 3D frame model of the face. By recognizing the facial expressions from facial images, a number of applications in the ?eld of human computer can be build. This paper describes about the working of Kinect and use of Kinect in Human Skeleton Tracking.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Skeleton Tracking Kinect Pose Estimation Arduino Actions