The use of facial images is widespread today. Popularization of the use of eye tracking systems, the field of observing facial images has become the subject of many researchers.
The purpose of our research was development a new combined method for the analysis of facial images, which would further verify the results of the analysis of facial images obtained by other methods. The first step was selection and preparation of facial images from chosen facial databases. Due to the variety of tests we have chosen two facial image bases: Minear & Park and Stirling.
At the beginning we performed time-spatial analyses with four different times and three different dimensions of the frontal facial images. The results of observing facial images in relation to recognition success were presented by combined method which consist previously known timespatial method and the newly designed area method. Additional results we obtained with facial features method and method of measuring response times in recognition process. All the results showed us the turning point in observing face images at four seconds observation time and
indicated potential problems of use of eye tracking systems for small dimensions of facial images.
These results were used for the preparation of profile facial image tests, where we used only two different dimensions of facial images (medium and large). Comparison of the recognition of front and profile facial images showed us a significant difference in results between frontal and profile facial images only in false recognition. The use of the combined method and the facial features method revealed a different way of observing profile facial images, where observing of whole face happened in a shorter time than that of the frontal facial images.
Next testing was done on faces presented at different view angles, where the results of combined method showed us different perception of those facial images.
The combined method was also tested in emotion recognition, where we found a great compliance of the area method and the facial features method. Since the facial features method has mainly confirmed the results of emotion recognition, we can also use the new surface method for emotion recognition.
The result of our research work is a combined method, part of which is a newly developed area method, which results supported the methods used so far in the analysis of facial images with eye tracking systems.
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