DocumentCode :
3752461
Title :
Fingertip Detection Using Two-Stage Random Decision Forest
Author :
Meng-Hsin Liu;Tai-Hung Lin;Chih-Wen Su
Author_Institution :
Dept. of Inf. &
fYear :
2015
Firstpage :
101
Lastpage :
104
Abstract :
In this study, we propose a new fingertip detection algorithm using two-stage random decision forest (RDF). In the first stage, local depth difference pattern (LDDP) and 3D geodesic shortest path (GSP) are adopted for training a finger pixel classifier. Two spatial and temporal features are then added into RDF to further distinguish fingertip pixels from finger pixels in the second stage. Finally, we utilize K-means clustering to re-identify fingertip candidates and limit the number of candidates to five. Our experimental result demonstrates that the proposed fingertip detection method is effective in complex gesture.
Keywords :
"Thumb","Three-dimensional displays","Image color analysis","Feature extraction","Resource description framework","Training"
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2015 International Conference on
Type :
conf
DOI :
10.1109/IIH-MSP.2015.67
Filename :
7415768
Link To Document :
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