We are going to split our work into three components:
1) Capturing the data from a live classroom
2) Running a face detection algorithm on all the frames in the video and generating the matrix of locations of audience.
3) Analyse the data thus obtained.
We are going to capture a video of a set of 40 people listening to a lecture of 60 minutes duration. We will provide our audience with a sheet of paper and ask them to rate the lecture every 5 minutes for 60 full minutes.
We will then see whether there exists a correlation between the audience rating every 5 minutes (average rating of all audience) and the head movement captured in the camcorder.
There are a couple of issues involved in this experiment:
a) How do we ensure that our audience rate the speaker every minute without fail?
b) Will there be a lot of head movement when the audience put their head down to rate the speaker every 5 minutes?
Your thoughts and inputs invited....
I personally believe this can be achieved in a much simpler way. Simpler in the sense that face detection algorithms are quite costly(time and resource). A class can be treated as a matrix with the number of elements of the matrix being each student. Analysing this 2 dimensional matrix can give the disturbance parameter. Is face detection algo necessary ? I don't think so.. Image processing yes .. face detection no ..
ReplyDeleteJust my thought !