/FD-Evaluation

Compact CNN cascade for face detection

Primary LanguageC++OtherNOASSERTION

Compact Convolutional Neural Network Cascade

Evaluation of frontal face detection algorithms

This is an implementation of the algorithm described in the following paper:

I.A. Kalinovskii, V.G. Spitsyn,
Compact Convolutional Neural Network Cascade for Face Detection,
http://arxiv.org/abs/1508.01292

This code used only for evaluation of face detectors on FDDB, AFW and IJB-A benchmarks or video data. It does not contain CNN detector. To view the test results it is necessary extract files from rar-archives to the root folder (Data/FDDB_TEST) and run the Matlab script.

If you use the provided code/binaries or data for your work, please cite this paper.

Demo video:

The precision detection can be increased by combination detectors.

№ method true false recall precision mean time, ms min time, ms max time, ms demo
1 Viola–Jones1 18679 3587 46.7% 83.9% 118 79 136 HD
2 Compact CNN 18788 908 47.0% 95.4% 12 10 17 HD
3 Compact CNN
(optimized for precision)		 16627 379 41.6% 97.8% 12 10 17
4 Hybrid2 (2 + 1) 16684 93 41.7% 99.4% 17 10 800 HD
1OpenCV 3.0.0 haarcascade frontalface alt for cuda
2without code optimization

Running on GPU Nvidia GeForce GT 640M
CPU Intel Core i7-3610QM (2.3GHz, without Turbo Boost)
Search settings: minSize – 40×40, scaleFactor – 1.2, minNeighbors – 2, without tracking

Contact

For any additional information contact me at kua_21@mail.ru.

Copyright (c) 2015, Ilya Kalinovskii. All rights reserved.