Paper Info
Title
Multiple fingertip detection under single camera with human computer interface applications
Abstract
This work proposes an accurate marker-less fingertip detection method under single camera. The moving skin regions are analyzed via enhanced mixture models. The models with adaptive learning rates can separate the backgrounds and moving skins effectively. For multiple fingertip detection, we propose an algorithm based on the likelihood computation of contour and curvature information. Furthermore, finger width validation and error correction via temporal information is used to improve the detection accuracy. The experiments have shown that the proposed method is robust and flexible. Finally, we implement a human computer interface system to test the effectiveness of the proposed framework.
Year
DOI
Venue
2016
10.1109/GCCE.2016.7800371
2016 IEEE 5th Global Conference on Consumer Electronics
Keywords
Field
DocType
Fingertip Detection,Human Computer Interface,Skin Region Analysis,Enhanced Mixture Models
Computer vision,Curvature,Computer science,Error detection and correction,Human–computer interaction,SKIN REGIONS,Artificial intelligence,Fingertip detection,Adaptive learning,Mixture model,Computation
Conference
ISBN
Citations 
PageRank 
978-1-5090-2334-9
0
0.34
References 
Authors
3
1
Name
Order
Citations
PageRank
Hsu-Yung Cheng124323.56