Viola Jones detektor lica#

Uzorak projekta Viola-Jones koji dolazi s CMUcam3 primjer je laganog detektora lica. Algoritam se temelji na poznatom radu „Robust Real-Time Face Detection” P. Viole i M. Jonesa iz 2004. (viola-ijcv04.pdf). Implementacija na CMUcam3 vratit će koordinate okvira gdje otkrije lice na slici. Ako testirate ovaj kod s relativno ujednačenom pozadinom (poput bijelog zida), radi razumno dobro. Slike su trenirane iz CMU baze podataka lica tako da se generaliziraju na sva lica. Ponekad određena lica sa značajkama koje se ne nalaze u bazi podataka mogu zbuniti detektor.

Sample Face 1 Sample Face 2

The paper (viola-ijcv04.pdf) introduces a novel technique to detect faces in real-time and with very high detection rate. It is essentially a feature-based approach in which a classifier is trained for Haar-like rectangular features selected by Adaboost. The test image is scanned at different scales and positions using a rectangular window, and the regions which pass the classifier are declared as faces. One of the major contributions of this paper is the extremely rapid computation of these features using the concept of Integral Image, which enables the detection in real-time. Additionally, instead of learning a single classifier and computing all the features for all the scanning windows in the image, a number of classifiers are learnt which are put together in a series to form a cascade. The classifiers in the beginning of the cascade are simpler and consist of smaller numbers of features. However, as one proceeds in the cascade, the classifiers become more complex. A region is reported as detection only if it passes all the classifier stages in the cascade. If it is rejected at any stage, it is discarded and not processed further. This way, the easier patches in the image which the „cascade of classifiers” is sure of not being a face, are rejected very early while the difficult regions are operated on by more complex classifiers. This greatly speeds up the detection process without compromising on the accuracy and provides high detection rate. This overall system provides performance comparable to the existing best face detector systems (Rowley et al., 1998 CVPR00.pdf; Schneiderman and Kanade, 2000 nips00.pdf; Roth at al., 2000 rowley-ieee.pdf) but with orders of magnitudes faster than any of these systems. On a conventional desktop, it can detect faces at 15 frames per second.

Više informacija o Viola-Jones detektoru lica i njegovoj CMUcam3 implementaciji možete pronaći u našem dokumentu CC3 detektor lica.

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