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Attractive Regions Extraction in Commercial Advertisement Based on Eye Tracking Analysis

Abstract

In the dynamic landscape of marketing, understanding consumer behavior and optimizing advertisement strategies are essential for success. This study investigates how eye tracking analysis can be help understanding the subtleties of customer behavior and find regions of interest influencing the creation of commercial advertisements.

The comprehensive methodology involves data collection, pre-processing, processing, and Points of Interest. Through eye tracking technology, participants’ gaze patterns are meticulously recorded as they engage with images. Subsequent stages encompass noise reduction, data categorization, point recurrence calculation, and identification of points of interest.

The findings present the significance of eye tracking in capturing visual attention patterns, shedding light on the areas that truly engage participants. Principal component analysis (PCA) is employed to Dimension reduction to get more accurate data.

Methodology applied to impose three regions of interest for each image. Presenting three images to a group of 20 participants the effectiveness which has been calculated of each image.

The data generated by the eye-tracking device was subjected to processing, and by calculating the region that contains the most points and the largest number of people who viewed it, the region with the most views and interest was determined.

By comparing the regions imposed as the most important for each image with the resulting regions, it was found that image number two obtained 90% percentage, which is the highest, while image number one obtained 87% percentage, and image number three obtained 70% percentage, which is the lowest.