Face detection considerations
Face recognition is actually a combination of face detection and face recognition. These two tasks work together.
In this post we are discussing face detection as a separate step. Refer to the post on "Better face suggestions" for a discussion of face recognition improvements planned.
If we continue to improve the accuracy of the face detector module, then that saves you time in two ways;
- avoiding having you delete "false positives" (not real faces)
- by not requiring that you add manual faces to correct "false negatives" (missed faces)
Factors in face detection include; resolution, lighting, pose, blur, occlusion.
Tips and tricks:
- our minimum face size is approx. 60 pixels in width
- generally it is less effort (keyboard clicks) to delete false positives then it is to uncover and add false negatives.
- one trick to note - by doubling the image size (simply by blowing it up) so that the smallest faces are greater than 60 pixels in width that can improve the results in most cases if faces are missed on small pixel sized images (roughly a min width of 800 pixels is something to shoot for). a good tool for that is XnConvert or XnResize - in the XnViewMP family.
Another tip is to enhance the quality of your images - if you are dealing with old scans. One tool available is available at MyHeritage - example enhancement steps below.
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