Hand Tracking Algorithm Based on SuperPixels Feature

Author

Zhiqin Zhang ; Fei Huang

Author_Institution

Sch. of Comput. Sci., Wuhan Donghu Univ., Wuhan, China

fYear

2013

fDate

7-8 Dec. 2013

Firstpage

629

Lastpage

634

Abstract

There have been considerable research efforts to use the hand as an input device for HCI in recent years. Hand tracking is the most important procedure for HCI, it is essential of tracking stability and efficiency for hand manipulation. This paper proposed a novel hand tracking algorithm which can track a hand stable and is real time, and the proposed algorithm can work on normal CCD cameral. Our algorithm is based on mean-shift and we improved it to fit for robust hand tracking by using super pixel cluster, integrated GIH and skin color mask, the skin color mask was extracted using online learning. The proposed improved algorithm can track hand reliably even in clutter environments comparing to the existing traditional algorithms.

Keywords

CCD image sensors; feature extraction; human computer interaction; image colour analysis; learning (artificial intelligence); object tracking; skin; HCI; clutter environments; hand manipulation; hand tracking algorithm; input device; integrated GIH; mean-shift based algorithm; normal CCD cameral; online learning; skin color mask extraction; super pixel cluster; super-pixel feature; tracking efficiency; tracking stability; Algorithm design and analysis; Cameras; Color; Feature extraction; Image color analysis; Skin; Target tracking; HCI; hand tracking; mean shift; monocular; online learning; super pixels;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on

Conference_Location

Guangzhou

Type

conf

DOI

10.1109/ISCC-C.2013.77

Filename

6973662