Title
Real-time hand tracking by invariant hough forest detection Real-time hand tracking by invariant hough forest detection
Author
Faculty/Department
Faculty of Applied Engineering Sciences
Publication type
conferenceObject
Publication
Subject
Physics
Engineering sciences. Technology
Source (journal)
2012 IEEE international conference on image processing (ICIP 2012)
Source (book)
19th IEEE International Conference on Image Processing (ICIP), SEP 30-OCT 03, 2012, Lake Buena Vista, FL
Volume/pages
(2012) , p. 149-152
ISSN
1522-4880
ISBN
978-1-4673-2533-2
ISI
000319334900034
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
This paper proposes a robust real-time hand tracking approach by combining a discriminative random forest classifier with generative color based cues using a particle filter. The proposed detector is scale and rotation invariant and is able to overcome ambiguities and local maxima in the color based likelihood function in real-time. A new hand tracking dataset with manually annotated groundtruths is created and made freely available for research purposes. Thorough evaluation shows the robustness and advantages of our proposal compared to other state of the art object tracking methods.
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