FACE RECOGNITION AND VIDEO FACE TRACKING Deepa ...

When we have a large number of images in the training database, the
computational speed is expected to be faster in case of wavelet sub-bands and the success
percentage difference is expected to be slightly less than the face recognition using Eigen
faces.
Future enhancements for face recognition can be expanded to handle more than
16 images in the training database. Right now, adjusting the given input images or test
images to the same resolution is a manual process. The program can be expanded to
adjust the image resolution automatically without manual involvement.
The face detection in the live video streaming is found to accurately detect human
face up to 7 feet. The video frame capturing interval is kept as 500 milliseconds. So every
500 milliseconds, the frame is captured and the face detection algorithm is run.
The video frame capturing interval can be made configurable. For example, in a
computer with a very fast processing speed, we can keep the interval smaller. If it is a
computer with lower processing speed, we can keep the interval higher. This parameter
could be read from a file instead of hard-wired value in the program.
Another future enhancement could be to combine both video face detection and
face recognition methods to not only detect a face in a video, but also recognize matching
face in the test database using wavelet sub-bands.
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