Viola Jones 人臉偵測器#

隨 CMUcam3 附帶的 Viola-Jones 範例專案是一個輕量級人臉偵測器的範例。此演算法以 P. Viola 與 M. Jones 於 2004 年發表的知名論文〈Robust Real-Time Face Detection〉為基礎（viola-ijcv04.pdf）。CMUcam3 上的實作會在影像中偵測到人臉之處回傳方框的座標。如果您以相對均勻的背景（例如白牆）測試這段程式碼，它的運作效果相當不錯。這些影像是從 CMU 人臉資料庫訓練而來，以便能泛化至所有人臉。有時某些具有資料庫中所沒有的特徵的臉孔會使偵測器混淆。

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.

有關 Viola-Jones 人臉偵測器及其 CMUcam3 實作的更多資訊，可在我們的 CC3 人臉偵測器 文件中找到。

額外的工具程式與影像