# A Survey on Eye-Gaze Tracking Techniques

arXiv: https://arxiv.org/abs/1312.6410 · HTML: https://mlsanity.com/paper/1312.6410/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2013.

## Built on by (most cited first, 4 of 4)

- [Automatic Gaze Analysis: A Survey of Deep Learning based Approaches](https://mlsanity.com/paper/2108.05479/) (2021)
- [AutoFocus-IL: VLM-based Saliency Maps for Data-Efficient Visual Imitation Learning without Extra Human Annotations](https://mlsanity.com/paper/2511.18617/) (2025)
- [Eye Gaze Estimation Model Analysis](https://mlsanity.com/paper/2207.14373/) (2022)
- [Modular Deep Learning Framework for Assistive Perception: Gaze, Affect, and Speaker Identification](https://mlsanity.com/paper/2511.20474/) (2025)

## Abstract (arXiv)

Study of eye-movement is being employed in Human Computer Interaction (HCI) research. Eye - gaze tracking is one of the most challenging problems in the area of computer vision. The goal of this paper is to present a review of latest research in this continued growth of remote eye-gaze tracking. This overview includes the basic definitions and terminologies, recent advances in the field and finally the need of future development in the field.