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Motion field segmentation and appearance change detection for hand tracking from the ego perspective

: Hammer, J.H.

Volltext urn:nbn:de:0011-n-3262624 (132 KByte PDF)
MD5 Fingerprint: 097d3d6e7174dcec0ee3f6ea824fdb98
Erstellt am: 11.2.2015

Beyerer, Jürgen (Ed.); Pak, Alexey (Ed.):
Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory 2013. Proceedings : July, 21 - 27, 2013, Triberg-Nussbach in Germany
Karlsruhe: KIT Scientific Publishing, 2014 (Karlsruher Schriften zur Anthropomatik 17)
ISBN: 978-3-7315-0212-8
ISBN: 3-7315-0212-7
DOI: 10.5445/KSP/1000040668
Fraunhofer Institute of Optronics, System Technologies and Image Exploitation and Institute for Anthropomatics, Vision and Fusion Laboratory (Joint Workshop) <2013, Triberg-Nussbach>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

In this paper a novel method for moving object tracking is presented and applied in the context of hand tracking for mobile Augmented-Reality (AR) applications. AR glasses-like devices come with an integrated camera capturing the field of view of the user. Hand gestures are the most intuitive interaction modality for manipulating AR contents and hand tracking is the first step towards robust gesture recognition. The presented method fuses motion segmentation and appearance change detection in a new way to track hands in front of complex backgrounds under varying lighting conditions - without the need for previous color calibration. A comparison of this new algorithm with state-of-the-art tracking methods is conducted using a thorough evaluation methodology and challenging data sets containing different wiping hand gestures.