viola-jones

Wanted to ask if there was any kind of face detection scheme suitable for video that would require minimal training time ideally about a few days rather than weeks like the Viola-Jones. I have read about LBP but it requires a huge set of training samples too but not sure how long it takes. Does training an LBP consume as much time as the Viola - Jones method with a similar number of training set ?. I will be implementing this on a microprocessor like raspberry pi running on a linux OS. Will want to implement it on C for speed as I want it to be able to detect images in a 10fps - 20fps video

Please explain to me, in few words, how the Viola-Jones face detection method works. cMinor The Viola-Jones detector is a strong, binary classifier build of several weak detectors Each weak detector is an extremely simple binary classifier During the learning stage, a cascade of weak detectors is trained so as to gain the desired hit rate / miss rate (or precision / recall) using Adaboost To detect objects, the original image is partitioned in several rectangular patches, each of which is submitted to the cascade If a rectangular image patch passes through all of the cascade stages, then it is

I've been implementing an adaptation of Viola-Jones' face detection algorithm . The technique relies upon placing a subframe of 24x24 pixels within an image, and subsequently placing rectangular features inside it in every position with every size possible. These features can consist of two, three or four rectangles. The following example is presented. They claim the exhaustive set is more than 180k (section 2): Given that the base resolution of the detector is 24x24, the exhaustive set of rectangle features is quite large, over 180,000 . Note that unlike the Haar basis, the set of rectangle