كاشف الوجوه Viola Jones#

مشروع Viola-Jones النموذجي الذي يأتي مع CMUcam3 هو مثال على كاشف وجوه خفيف. تستند الخوارزمية إلى الورقة البحثية المعروفة "Robust Real-Time Face Detection" لـ P. Viola وM. Jones من عام 2004 (viola-ijcv04.pdf). سيُعيد التنفيذ على CMUcam3 إحداثيات مربعات حيث يكتشف وجهًا في الصورة. إذا اختبرت هذا الكود بخلفية موحدة نسبيًا (مثل جدار أبيض)، فإنه يعمل بشكل جيد إلى حد معقول. الصور مدربة من قاعدة بيانات وجوه CMU بحيث تُعمَّم على كل الوجوه. أحيانًا يمكن لوجوه معينة ذات ملامح غير موجودة في قاعدة البيانات أن تربك الكاشف.

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.

يمكن العثور على مزيد من المعلومات حول كاشف الوجوه Viola-Jones وتنفيذه على CMUcam3 في مستند CC3 Face Detector الخاص بنا.

أدوات وصور إضافية

  • generate_feat_in_struct_for_C.m

    • يطبع ملف Matlab هذا نموذج adaboost المتعلَّم في ملف نصي بحيث يمكن استيراده بسهولة في vj.h

  • get_scaled_feature.m

    • هذا الملف يستخدمه generate_feat_in_struct_for_C.m

  • الصور الاختبارية التي استخدمناها لكاشف الوجوه viola-jones