Name
Abstract | ||
|---|---|---|
Gender recognition is a challenging task in real life images and surveillance videos due to their relatively low-resolution, under uncontrolled environment and variant viewing angles of human subject. Therefore, in this paper, a system of real-time gender recognition for real life images is proposed. The contribution of this work is three-fold. In order to make the system robust, a mechanism of decision making based on the combination of surrounding face detection, context-regions enhancement and confidence-based weighting assignment is designed. Experiment results obtained by using extensive dataset show that our system is effective and efficient in recognizing genders for uncontrolled environment of real life images. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/TCE.2010.5606301 | IEEE Transactions on Consumer Electronics |
Keywords | Field | DocType |
real life image,uncontrolled environment,gender recognition,real-time gender recognition,challenging task,confidence-based weighting assignment,context-regions enhancement,experiment result,extensive dataset show,face detection,real-life image,robust gender recognition | Computer vision,Computer science,Artificial intelligence | Conference |
Volume | Issue | ISSN |
56 | 3 | 0098-3063 |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Duan-Yu Chen | 1 | 296 | 28.79 |
| Kuan-Yi Lin | 2 | 6 | 1.77 |