Name
Abstract | ||
|---|---|---|
In this paper we present a semiautomatic method for skin identification in video sequences. The user trains the system by selecting in a frame some typical positive skin pixels, that will be used as a reference for the construction of a nonlinear distance metric. In this learning process the global optimum is obtained by induction employing higher polynomial terms of the Mahalanobis distance, extracting nonlinear features of the skin pattern distributions. These nonlinear features are then used to classify the frames captured from the camera, identifying all skin and non-skin regions on the scene. We adopt an estrategy which enables this method to run in real-time after some iteractions. We also compare our classification method against vector norm (L-2) and Mahalanobis distance, showing a better classification for the skin patterns. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-12568-8_18 | PROGRESS IN PATTERN RECOGNITION IMAGE ANALYSIS, COMPUTER VISION, AND APPLICATIONS, CIARP 2014 |
Field | DocType | Volume |
Computer vision,Scale-space segmentation,Color space,Pattern recognition,Segmentation,Computer science,Metric (mathematics),Mahalanobis distance,Image segmentation,Pixel,Artificial intelligence,Norm (mathematics) | Conference | 8827 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
8 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Carlos Sobieranski | 1 | 11 | 4.23 |
| Vito F. Chiarella | 2 | 0 | 0.34 |
| Eduardo Barreto-Alexandre | 3 | 5 | 0.75 |
| Rodrigo Linhares | 4 | 8 | 2.27 |
| Eros Comunello | 5 | 66 | 15.04 |
| Aldo von Wangenheim | 6 | 209 | 49.44 |