Pendeteksi Wajah Viola Jones#

Proyek contoh Viola-Jones yang disertakan dengan CMUcam3 adalah contoh pendeteksi wajah ringan. Algoritmanya didasarkan pada makalah terkenal "Robust Real-Time Face Detection" oleh P. Viola dan M. Jones dari tahun 2004 (viola-ijcv04.pdf). Implementasi pada CMUcam3 akan mengembalikan koordinat untuk kotak-kotak di mana ia mendeteksi wajah dalam gambar. Jika Anda menguji kode ini dengan latar belakang yang relatif seragam (seperti dinding putih), ia bekerja cukup baik. Gambar-gambar dilatih dari basis data wajah CMU sehingga dapat menggeneralisasi ke semua wajah. Kadang-kadang wajah tertentu dengan fitur yang tidak ditemukan dalam basis data dapat membingungkan pendeteksi.

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.

Informasi lebih lanjut tentang pendeteksi wajah Viola-Jones dan implementasi CMUcam3-nya dapat ditemukan dalam dokumen CC3 Face Detector kami.

Utilitas dan Gambar Tambahan