[D] Real-time Student Attention Detection: ResNet vs Facial Landmarks - Which approach for resource-constrained deployment?

I have a problem statement where we are supposed to detect the attention level of student in a classroom, basically output whether he is engaged/ confused/ bored, we are trying to find what approach to choose: to basically explain about facial landmarks approach this is what my claude says: Facial landmarks are specific coordinate points (x, y) that map key features on a face. The standard model uses 68 points that outline the jawline, eyebrows, eyes, nose, and mouth. This approach has roots in traditional computer vision and is based on geometric measurements rather than pixel patterns.