A searchable list of some of my publications is below. You can also access my publications from the following sites.
My ORCID is
https://orcid.org/0000-0002-6236-2969
Publications:
1.
Ravi Ruddarraju, Antonio Haro, Kris Nagel, Quan Tran, Irfan Essa, Gregory Abowd, Elizabeth Mynatt
Perceptual User Interfaces using Vision-Based Eye Tracking Proceedings Article
In: International Conference on Multimodal Interfaces (ICMI), Vancouver, Canada, 2003.
@inproceedings{2003-Ruddarraju-PUIUVT,
title = {Perceptual User Interfaces using Vision-Based Eye Tracking},
author = {Ravi Ruddarraju and Antonio Haro and Kris Nagel and Quan Tran and Irfan Essa and Gregory Abowd and Elizabeth Mynatt},
url = {https://doi.org/10.1145/958432.958475},
doi = {10.1145/958432.958475},
year = {2003},
date = {2003-01-01},
urldate = {2003-01-01},
booktitle = {International Conference on Multimodal Interfaces (ICMI)},
address = {Vancouver, Canada},
abstract = {We present a multi-camera vision-based eye tracking method to robustly locate and track user's eyes as they interact with an application. We propose enhancements to various vision-based eye-tracking approaches, which include (a) the use of multiple cameras to estimate head pose and increase coverage of the sensors and (b) the use of probabilistic measures incorporating Fisher's linear discriminant to robustly track the eyes under varying lighting conditions in real-time. We present experiments and quantitative results to demonstrate the robustness of our eye tracking in two application prototypes.
},
keywords = {computer vision, eye-tracking, ICMI, multimodal interfaces},
pubstate = {published},
tppubtype = {inproceedings}
}
We present a multi-camera vision-based eye tracking method to robustly locate and track user's eyes as they interact with an application. We propose enhancements to various vision-based eye-tracking approaches, which include (a) the use of multiple cameras to estimate head pose and increase coverage of the sensors and (b) the use of probabilistic measures incorporating Fisher's linear discriminant to robustly track the eyes under varying lighting conditions in real-time. We present experiments and quantitative results to demonstrate the robustness of our eye tracking in two application prototypes.
2.
A. Haro, I. Essa, M. Flickner
A Non-Invasive Computer Vision System For Reliable Eye Tracking Proceedings Article
In: Szwillus, G., Turner, T. (Ed.): ACM CHI Conference on Human factors in Computing Systems, pp. 167–168, ACM ACM press, 2000.
@inproceedings{2000-Haro-NCVSRT,
title = {A Non-Invasive Computer Vision System For Reliable Eye Tracking},
author = {A. Haro and I. Essa and M. Flickner},
editor = {G. Szwillus and T. Turner},
doi = {10.1145/633292.633385},
year = {2000},
date = {2000-04-01},
booktitle = {ACM CHI Conference on Human factors in Computing Systems},
pages = {167--168},
publisher = {ACM press},
organization = {ACM},
abstract = {Knowing what the user is attending to and what they are looking at is essential for creating attentive user interfaces. Towards this end, we are building a reliable, real-time, non-invasive eye tracker using computer vision. Our system can robustly locate and track eyes without any calibration, and estimate the user's focus of attention. We have built several higher-level processes on top of this tracking system and have done some user studies to test the viability of our approach.},
keywords = {eye-tracking},
pubstate = {published},
tppubtype = {inproceedings}
}
Knowing what the user is attending to and what they are looking at is essential for creating attentive user interfaces. Towards this end, we are building a reliable, real-time, non-invasive eye tracker using computer vision. Our system can robustly locate and track eyes without any calibration, and estimate the user's focus of attention. We have built several higher-level processes on top of this tracking system and have done some user studies to test the viability of our approach.
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