A hybrid method using kinect depth and color data stream for hand blobs segmentation

Karbasi, Mostafa and Muhammad Yusof, Zulkefli and Waqas, Ahmad and Bhatti, Zeeshan and Shah, Asadullah and Koondhar, M.Y. and Brohi, Imtiaz Ali (2017) A hybrid method using kinect depth and color data stream for hand blobs segmentation. Science International, 29 (3 (May-June)). pp. 515-519. ISSN 1013-5316

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Abstract

The recently developed depth sensors such as Kinect have provided new potential for human-computer interaction (HCI) and hand gesture are one of main parts in recent researches. Hand segmentation procedure is performed to acquire hand gesture from a captured image. In this paper, a method is produced to segment hand blobs using both depth and color data frames. This method applies a body segmentation and an image threshold techniques to depth data frame using skeleton data and concurrently it uses SLIC super-pixel segmentation method to extract hand blobs from color data frame with the help of skeleton data. The proposed method has low computation time and shows significant results when basic assumption are fulfilled.

Item Type:	Article (Journal)
Additional Information:	6566/58448
Uncontrolled Keywords:	hand gesture recognition, human computer interaction, simple linear iterative clustering (SLIC), hand detection, posture recognition
Subjects:	T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Prof Asadullah Shah
Date Deposited:	21 Sep 2017 10:52
Last Modified:	04 Jan 2018 10:22
URI:	http://irep.iium.edu.my/id/eprint/58448

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