Publication
Title
Real-time hand tracking by invariant hough forest detection
Author
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.
Language
English
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
Publication
2012
Volume/pages
(2012), p. 149-152
ISI
000319334900034
Number
978-1-4673-2533-2
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 10.09.2013
Last edited 30.03.2017
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