Detetor de Rostos Viola Jones#

O projeto de exemplo Viola-Jones que vem com a CMUcam3 é um exemplo de um detetor de rostos leve. O algoritmo baseia-se no conhecido artigo «Robust Real-Time Face Detection» de P. Viola e M. Jones, de 2004 (viola-ijcv04.pdf). A implementação na CMUcam3 devolverá coordenadas para caixas onde deteta um rosto na imagem. Se testar este código com um fundo relativamente uniforme (como uma parede branca), funciona razoavelmente bem. As imagens são treinadas a partir da base de dados de rostos da CMU de forma a generalizarem para todos os rostos. Por vezes, certos rostos com características não encontradas na base de dados podem confundir o detetor.

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.

Pode encontrar mais informações sobre o detetor de rostos Viola-Jones e a sua implementação na CMUcam3 no nosso documento CC3 Face Detector.

Utilitários e Imagens Extra