Experimental results

We made a lot of experiments with different face databases and with real signal from video camera. In most cases (~85 %) face detection system achieved quite good performance with default parameters. Main problems occurred while detecting rotated faces, faces of people, wearing glasses, faces with not good lighting conditions (lamp on the floor beyond the face).

Example of successful face detection procedure is shown on the figure below. Face region is shown with yellow circle and eyes – with two yellow crosses.

Fig. Example of successful face detection

Let’s say some words about the indicated problems. Noninvariance to the turning of the head is main deficiency of Viola-Jones detector. So we cannot detect faces if it is rotated more than on 15º. But firstly almost all existing algorithms of face detection have this deficiency and secondly noninvariance to the turning is not main requirement to our system. Faces of people wearing glasses could be successfully recognized using alternative cascade file, trained on faces such a people. Lighting conditions are to be not very bad, i.e. face are to be discernible, focally and lighted.

We also tested different face detection algorithms such as morphologically-based face parts detection and skin-color based face detection. This algorithms work quiet well on rather good images (i.e. high quality contrasted images of human faces without background etc.). But when we tested these algorithms on more real images, in many cases they couldn’t detect anything. So these algorithms cannot be used on their own in contrast to Viola-Jones detector.

Conclusions

Different methods of face detection were analyzed and Viola-Jones detector was chosen as the most appropriate for out task. Parameters of this detector were set so that quality of face detection was good. Experiments showed some drawbacks of the Viola-Jones detector but most of them were expected.