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Update README.md

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Andreas Bulling 2016-03-11 13:38:39 +01:00
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@ -18,19 +18,19 @@ published at ETRA 2016
> code/results -> Contains gaze estimation results for both 2D-to-2D and 2D-to-3D mapping approaches with multiple calibration depths on data from participants. data files in the root directory of each method correspond to single depth calibration results. data format is described inside README.txt inside each method directory. the results are also available via /BS/3D_Gaze_Tracking/work/results
> code/Visualization -> Creation of figures for the paper
>> `python 1CalibrationDepth.py` -> 2D-to-2D vs. 2D-to-3D with one calibration depth
> `python 1CalibrationDepth.py` -> 2D-to-2D vs. 2D-to-3D with one calibration depth
>> `python 3CalibrationDepths.py` -> 2D-to-2D vs. 2D-to-3D with three calibration depth
> `python 3CalibrationDepths.py` -> 2D-to-2D vs. 2D-to-3D with three calibration depth
>> `python EffectDistanceDifference1CalibrationDepth.py` -> Effect of different distances to the original calibration depth
> `python EffectDistanceDifference1CalibrationDepth.py` -> Effect of different distances to the original calibration depth
>> `python EffectNumberofClusters.py` -> Effect of the number of clusters
> `python EffectNumberofClusters.py` -> Effect of the number of clusters
### Publication
If you use or extend our code, please cite the following paper:
> *Mansouryar, Mohsen, et al. "3D Gaze Estimation from 2D Pupil Positions on Monocular Head-Mounted Eye Trackers." Proc. of the 9th ACM International Symposium on Eye Tracking Research & Applications (ETRA 2016). http://dx.doi.org/10.1145/2857491.2857530*
Mansouryar, Mohsen, et al. "3D Gaze Estimation from 2D Pupil Positions on Monocular Head-Mounted Eye Trackers." *Proc. of the 9th ACM International Symposium on Eye Tracking Research & Applications (ETRA 2016)*. http://dx.doi.org/10.1145/2857491.2857530
## Dependencies