Viola Jones 人脸检测器#

CMUcam3 附带的 Viola-Jones 示例项目是一个轻量级人脸检测器的例子。该算法基于 P. Viola 和 M. Jones 于 2004 年发表的著名论文"Robust Real-Time Face Detection"（viola-ijcv04.pdf）。CMUcam3 上的实现将返回它在图像中检测到人脸的框的坐标。如果您在相对均匀的背景（如白墙）下测试此代码，它工作得相当好。这些图像是从 CMU 人脸数据库训练的，因此它们可以推广到所有人脸。有时某些具有数据库中未找到的特征的人脸会使检测器混淆。

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.

有关 Viola-Jones 人脸检测器及其 CMUcam3 实现的更多信息，可在我们的 CC3 人脸检测器 文档中找到。

额外的实用工具和图像