Viola Jones 얼굴 검출기#

CMUcam3와 함께 제공되는 Viola-Jones 샘플 프로젝트는 경량 얼굴 검출기의 예입니다. 이 알고리즘은 2004년 P. Viola와 M. Jones의 잘 알려진 논문 “Robust Real-Time Face Detection”(viola-ijcv04.pdf)을 기반으로 합니다. CMUcam3의 구현은 이미지에서 얼굴을 검출하는 상자의 좌표를 반환합니다. 비교적 균일한 배경(흰 벽 같은)으로 이 코드를 테스트하면, 상당히 잘 작동합니다. 이미지는 모든 얼굴에 일반화되도록 CMU 얼굴 데이터베이스에서 훈련됩니다. 때때로 데이터베이스에서 발견되지 않는 특징을 가진 특정 얼굴은 검출기를 혼란시킬 수 있습니다.

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.

Viola-Jones 얼굴 검출기와 그 CMUcam3 구현에 대한 자세한 내용은 저희의 CC3 Face Detector 문서에서 찾을 수 있습니다.

추가 유틸리티 및 이미지