offset). This ensures the machine can recognize when a gesture starts, peaks in intensity, and ends. 5. Fuse Multi-modal Data
Gunes’s work often emphasizes , where facial features are combined with other modalities like body gestures or audio markers (e.g., MFCCs) to improve the accuracy of emotion recognition. ✅ Result offset)
The generated feature is a (such as a 2D head motion angle) that allows a system to classify human affective states or non-verbal behaviors. Project suggestions from Prof Hatice Gunes peaks in intensity