Feature Extraction Techniques For Facial Micro-Expression Recognition
Feature extraction techniques play a significant role in many computer vision tasks such as detection and recognition. To be able to effectively describe targets, a suitable feature extraction method has to be applied. In this research work, the main goal is to design or formulate the feature extract...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
2016
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Feature extraction techniques play a significant role in many computer vision tasks such as detection and recognition. To be able to effectively describe targets, a suitable feature extraction method has to be applied. In this research work, the main goal is to design or formulate the feature extraction techniques for facial micro-expression recognition. Subtle emotions possess distinct characteristics compared to the normal facial expressions in a few aspects: elapsed duration and motion intensity. For facial micro-expressions, they are subtle (i.e. less intensive or obvious facial motion changes) and short elapsed duration. Thus, to capture subtle emotions, the designed features have to be able to: (1) contain both spatial and temporal information and (2) preserve the locality information (as facial micro-expressions usually occur at one part of a face). This dissertation introduces three proposed spatio-temporal feature extraction techniques for facial micro-expression recognition based on videos. |
|---|