| Budget Amount *help |
¥19,890,000 (Direct Cost: ¥15,300,000、Indirect Cost: ¥4,590,000)
Fiscal Year 2019: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2018: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2017: ¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥5,460,000 (Direct Cost: ¥4,200,000、Indirect Cost: ¥1,260,000)
|
|---|
| Outline of Final Research Achievements |
The aim of this project was to develop facial expression recognition technology using an embedded optical sensor array and machine learning, which enables facial expression recognition in a head-mounted display (HMD). Facial expression recognition in an HMD with an ordinal camera system is challenging due to occlusions. We developed a method for detecting basic facial expressions and extended it to estimate the intensity of each facial expression. We have shown that synthesized expressions can be rendered on avatars in a virtual environment. In addition to identifying the basic expression classes, we confirmed that it is possible to reconstruct high-dimensional 3D positions of feature points on a facial surface from the low-dimensional sensor values. Furthermore, we demonstrated that facial expression recognition accuracy was improved by making a training dataset that incorporates gaze and head direction as a machine learning method robust to the diversity of facial expressions.
|
