Name
Title | ||
|---|---|---|
Evolving an emotion recognition module for an intelligent agent using genetic programming and a genetic algorithm |
Abstract | ||
|---|---|---|
Most studies use the facial expression to recognize a useru0027s emotion; however, gestures, such as nodding, shaking the head, or stillness can also be indicators of the useru0027s emotion. In our research, we use the facial expression and gestures to detect and recognize a useru0027s emotion. The pervasive Microsoft Kinect sensor captures video data, from which several features representing facial expressions and gestures are extracted. An in-house extensible markup language-based genetic programming engine (XGP) evolves the emotion recognition module of our system. To improve the computational performance of the recognition module, we implemented and compared several approaches, including directed evolution, collaborative filtering via canonical voting, and a genetic algorithm, for an automated voting system. The experimental results indicate that XGP is feasible for evolving emotion classifiers. In addition, the obtained results verify that collaborative filtering improves the generality of recognition. From a psychological viewpoint, the results prove that different people might express their emotions differently, as the emotion classifiers that are evolved for particular users might not be applied successfully to other user(s). |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s10015-016-0263-z | Artificial Life and Robotics |
Keywords | DocType | Volume |
Emotion recognition, Facial expression, Genetic programming, Gestures | Journal | 21 |
Issue | ISSN | Citations |
1 | 1614-7456 | 3 |
PageRank | References | Authors |
0.46 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rahadian Yusuf | 1 | 5 | 2.93 |
| Dipak Gaire Sharma | 2 | 3 | 0.46 |
| Ivan Tanev | 3 | 278 | 46.51 |
| Katsunori Shimohara | 4 | 327 | 106.53 |