Name
Abstract | ||
|---|---|---|
•Common feature extraction methods are tested on a benchmark dataset.•Experimental results are presented with recognition rate and computational cost.•A multi-objective analysis and optimization is applied to gesture recognition.•A real-time gesture recognition system is implemented. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.eswa.2017.09.046 | Expert Systems with Applications |
Keywords | Field | DocType |
Sign language,Gesture recognition,Feature selection | Computer vision,Feature vector,Evolutionary algorithm,Three-dimensional face recognition,Computer science,Gesture recognition,Multilayer perceptron,Sketch recognition,Artificial intelligence,Artificial neural network,Genetic algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
92 | C | 0957-4174 |
Citations | PageRank | References |
6 | 0.55 | 22 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergey A. Chevtchenko | 1 | 6 | 0.55 |
| Rafaella F. Vale | 2 | 6 | 0.55 |
| Valmir Macario | 3 | 12 | 2.43 |