Goal: environment lighting independent face detection from the webcam video stream.
The red and blue subspace is used to reduce the illumination noise. Since the skin texture for fac eis dependent on the illumination condition. The illumination condition is identified first and then face texture pattern is modeled using 10 examples for each illumination condition. Motion detection technique is used to eliminate color region similar to face in the background.
Iris gives out luminance and its detected using the sharp change in the Y component.
Discussion:
Statistics on accuracy is not given. The KNN classifier would be drastically slow in case of more examples. Each illumination setting requires a set of examples to be provided. How do we enumerate all the illumination setting ? I do not think the recognition algorithm would scale to settings that has no examples.
It would have been nice to have some data as to how it was determined that the system performed. Your comment on KNN and speed is interesting.
ReplyDeleteI did not know KNN would be slower with more examples. It is a good point.
ReplyDeleteI think I ran into what you mentioned about not having examples for the KNN in my other project. I didn't think KNN would work in this scenario.
ReplyDelete