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Samuel Cahyawijaya
Informatics Engineering, Institut Teknologi Bandung
Computer Science & IT Electrical & Electronics Engineering

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Automatic Human Joint Detection Using Microsoft Kinect Samuel Cahyawijaya; Iping Supriana Suwardi
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 1: EECSI 2014
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1027.038 KB) | DOI: 10.11591/eecsi.v1.351

Abstract

Automatic human joint detection has been used in many application nowadays. In this paper, we propose an approach to detect full body human joint method using depth and color image. The proposed solution is divided into 3 stage, which is image preprocess stage, distance transform stage, and anthropometric constraint analysis stage. The output of our solution is a stickman model with the same pose as in the given input image. Our implementation is done by using a Microsoft Kinect RGB and depth camera with 480x640 image resolution. The performance of this solution is demonstrated on several human posture.
Co-Authors Iping Supriana Suwardi