You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
We introduce and evaluate a novel approach for detecting smooth pursuit eye movements that increases the number of distinguishable targets and is more robust against false positives. Being natural and calibration-free, Pursuits has been gaining popularity in the past years. At the same time, current implementations show poor performance when more than eight on-screen targets are being used, thus limiting its applicability. Our approach (1) leverages the slope of a regression line, and (2) introduces a minimum signal duration that improves both the new and the traditional detection method. After introducing the approach as well as the implementation, we compare it to the traditional correlation-based Pursuits detection method. We tested the approach up to 24 targets and show that, if accepting a similar error rate, nearly twice as many targets can be distinguished compared to state of the art. For fewer targets, accuracy increases significantly. We believe our approach will enable more robust pursuit-based user interfaces, thus making it valuable for both researchers and practitioners.

Cited Abstract(s):
[1]: SmoothMoves is an interaction technique for augmented reality (AR) based on smooth pursuits head movements. It works by computing correlations between the movements of on-screen targets and the user's head while tracking those targets. The paper presents three studies. The first suggests that head based input can act as an easier and more affordable surrogate for eye-based input in many smooth pursuits interface designs. A follow-up study grounds the technique in the domain of augmented reality, and captures the error rates and acquisition times on different types of AR devices: head-mounted (2.6 , 1965ms) and hand-held (4.9 , 2089ms). Finally, the paper presents an interactive lighting system prototype that demonstrates the benefits of using smooth pursuits head movements in interaction with AR interfaces. A final qualitative study reports on positive feedback regarding the technique's suitability for this scenario. Together, these results indicate show SmoothMoves is viable, efficient and immediately available for a wide range of wearable devices that feature embedded motion sensing.

[2]: 

[3]: Eye tracking technology in a head-mounted display has undergone rapid advancement in recent years, making it possible for researchers to explore new interaction techniques using natural eye movements. This paper explores three novel eye-gaze-based interaction techniques: (1) Duo-Reticles, eye-gaze selection based on eye-gaze and inertial reticles, (2) Radial Pursuit, cluttered-object selection that takes advantage of smooth pursuit, and (3) Nod and Roll, head-gesture-based interaction based on the vestibulo-ocular reflex. In an initial user study, we compare each technique against a baseline condition in a scenario that demonstrates its strengths and weaknesses.
Pursuits were also used in mixed reality. VR benefits from using Pursuits during interaction, especially when moving in VR [2] , and when interacting with occluded targets [3] . Pursuits was also employed in augmented reality glasses [1] .