Systematic Performance Evaluation of WebGazer Webcam-Based Eye Tracking with Spatial and Angular Error Analysis

Eye tracking technologies have become increasingly accessible through webcam-based solutions such as WebGazer, enabling large-scale and low-cost experimentation. However, their performance remains sensitive to several experimental and device-related parameters. This study presents a controlled experimental framework developed to systematically evaluate WebGazer under configurable experimental conditions. Within this framework, we design and implement a controlled experimental protocol to investigate the effect of key parameters, including (i) joint calibration/evaluation point-density configuration, (ii) evaluation-point distribution, (iii) target presentation duration, (iv) stimulus color, and (v) stimulus (target) size. WebGazer's performance is assessed using both device-pixel spatial error metrics and angular error (delta), providing complementary measures of gaze accuracy. Results from 20 participants show that denser point configurations were associated with lower mean spatial error, from 1383 to 1009 device pixels, and lower mean angular error, from 13.556 to 10.322 degrees, within the tested conditions. Across the aggregated condition summaries, the joint point-density configuration showed the widest spatial-error range, whereas target presentation duration showed the widest angular-error range. Taken together, these two factors displayed the clearest descriptive differences, followed by evaluation-point distribution. Pseudo-random layouts were associated with moderately higher errors than fixed layouts. In contrast, visual properties such as color and size showed comparatively smaller and less consistent differences, with stimulus size displaying a non-monotonic pattern. Overall, temporal and calibration-related settings showed the clearest descriptive associations with WebGazer performance, while visual design choices showed smaller differences. This study provides a practical quantitative framework for systematically assessing webcam-based eye tracking systems under realistic usage conditions.