# Appearance-Based Gaze Estimation as a Benchmark for Eye Image Data Generation Methods
## Appendix D Blender image rendering parameters  
The first Blender set was used for training all image generation networks. One of the goals of the trained generative framework was to produce data covering a wide range of features, complementary to the variability present in real data. The following parameter values were utilized within the rendering pipeline (the values were sampled randomly, where \(U\), \(N\) stand for uniform and normal distributions, respectively):  
* Camera position: \(U(\pm 2.5;\pm 2.5;\pm 5.0)\) mm--horizontal, vertical and depth-wise shift from the neutral position of \((0;0;0)\);
* Eye gaze: \(U(\pm 20.51^{\circ};\pm 16.7^{\circ})\)--covering the same range as in real data;  
\begin{table}
\begin{tabular}{|c c c c c|} \hline \hline
**Comparison** & \(\Delta\) in **Mean Error** & **DF** & \(t\)**-Value** & \(p\)**-Value** \\ \hline I vs. II & 6.35 & 544 & 7.090 & \(<\)0.0001 \\ \hline I vs. V & \(-3.54\) & 544 & \(-3.948\) & 0.0003 \\ \hline II vs. V & \(-9.88\) & 544 & \(-11.038\) & \(<\)0.0001 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The statistical analysis of difference between data augmentation methods (the roman numerals follow the order of methods in Figure 4).  
* Lighting conditions: a random omnidirectional point of light (i.e., light type \"sun\" in Blender 2.7) placed at \(\{x=U(-90.0;-45.0),y=-45.0,z=U(-90.0;-45.0)\}\) location and strength property sampled from \(U(1.0;10.0)\); a random single-directional point of light (i.e., light type \"led\" in Blender 2.7) with location and strength sampled from the same distributions, intended to simulate varying lighting conditions;
* Dark/bright iris: 50%/50% split (as only two iris textures were available in the original Blender model);
* Pupil radius: \(N(1.75;0.33)\) mm limited to the range of \([1.0\ldots 2.5]\);
* Blink: 5% chance with an eye \"closedness\" sampled from \(U(0.0;1.0)\).  
The parameters for generating the second Blender set were manually adjusted, taken from the real data of a corresponding subject, or sampled randomly. The central camera position was aligned manually for each subject, as described in the main text. The gaze samples directly followed the real eye movement recordings, which also means that the number of generated samples both per-subject and overall was the same as in the reduced VOG set. The randomness was implemented both on across-subject and within-subjects levels. The remaining parameters, namely, lighting sources strength, pupil size, iris color, and eye \"closedness\" during a blink, were all non-trivial to adjust on a per-sample basis using corresponding real samples as reference points. Instead, they were randomly sampled. The overall scheme of rendering parameters is summarized below:  
* Camera: manually adjusted per-subject base position + per-sample horizontal, vertical and depth shifts of \(N(0;0.1)\), \(N(0;0.05)\), \(N(0;0.25)\) (in mm), respectively;
* Eye gaze: taken from a corresponding sample of real VOG data for all subjects;
* Lighting conditions; Dark/bright iris: same parameters as in the first Blender set;
* Pupil radius: \(N(1.5;0.25)\) mm limited to the range of \([1.0\ldots 2.0]\);
* Blink: 0% chance (no blinks, as in the reduced VOG data set).