Name
Abstract | ||
|---|---|---|
This paper proposes an accurate moving skin region detection method for video-based human-computer interface using gestures or fingertips. Using Gaussian mixture models as groundwork, the proposed method expresses the features of skins in a probability form and incorporates them into the mixture-based framework. Moreover, to alleviate the influence of shadows, the properties of shadows are also formulated as probabilities and used for shadow detection and elimination. In addition to moving skin region detection, this paper also develops two practical fingertip input applications to demonstrate the accuracy of the proposed detection method. The two applications are Mandarin Phonetic Symbol combination recognition system and single fingertip virtual keyboard implementation. Experimental results have shown the advantages of the proposed detection method and the effectiveness of the two application implementations. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.jvcir.2013.05.009 | J. Visual Communication and Image Representation |
Keywords | Field | DocType |
application implementation,gaussian mixture model,practical fingertip input application,single fingertip virtual keyboard,shadow probability,skin region detection,proposed detection method,skin region detection method,mandarin phonetic symbol combination,shadow detection,mixture models,feature extraction,human computer interface | Computer vision,Shadow,Pattern recognition,Recognition system,Gesture,Feature extraction,Artificial intelligence,Virtual keyboard,Region detection,Mixture model,Mathematics | Journal |
Volume | Issue | ISSN |
24 | 7 | 1047-3203 |
Citations | PageRank | References |
0 | 0.34 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chih-Chang Yu | 1 | 32 | 8.93 |
| Hsu-Yung Cheng | 2 | 243 | 23.56 |
| Chien-cheng Lee | 3 | 174 | 15.60 |