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Received Nov 27; Accepted Feb This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article has been cited by other articles in PMC. Abstract Despite the availability of accurate, commercial gaze tracker devices working with infrared IR technology, visible light gaze tracking constitutes an interesting alternative by allowing scalability and removing hardware requirements.
Over the last years, this field has seen examples of research showing performance comparable to the IR alternatives. In this work, we survey the previous work on remote, visible light gaze trackers and analyze the explored techniques from various perspectives such as calibration strategies, head pose invariance, and gaze estimation techniques.
We also provide information on related aspects of research such as public datasets to test against, open source projects to build upon, and gaze tracking services to directly use in applications.
With all this information, we aim to provide the contemporary and future researchers Audison thesis v vento specs a map detailing previously explored ideas and the required tools.
Introduction From a computer scientist's perspective, human beings are machines which receive input from their sensors such as ears, eyes, and skin and which interact with the world they live in through their actuators, which are their hands, feet, and so on.
Their attention can be understood by analyzing the way they direct their sensors i. Moreover, as in the case of robots, examining this attention can give us hints about their state of mind and their way of reasoning.
Among the human senses, sight has an important place in today's world where we are surrounded with digital displays be it in our mobile phones, our computers, or televisions. Instead of making passive observations of the objects around, it also gives hints about what the person actively chooses to see through eye movements.
Analysis of these movements, therefore, sparked great interest in research communities. Devices or systems that track a person's eye movements are called eye trackers or gaze trackers. Currently, the most widespread techniques used in these trackers make use of light sources and cameras that operate in the infrared IR spectrum.
There are many available commercial models that are in the form of either eyeglasses or table mounted devices [ 1 — 3 ] and also open source alternatives that allow the use of custom hardware [ 4 ]. Visible light gaze tracking, on the other hand, does not require any special hardware and aims to solve the task making use of regular cameras.
In this paper, we will concentrate on this class of trackers and survey the related research. Furthermore, we will limit our search to the table mounted setup also called remote setup as it is ubiquitous in contemporary devices and it removes the restrictions for camera placement with a few exceptions.
Our aim and contribution is as follows: To provide an exhaustive literature review. To comment on these works from various perspectives.
To list publicly available datasets. To list open source software. To list gaze trackers as a web service. The rest of the paper is organized as follows: Then, we will categorize and explain the previous work according to the techniques used and continue with two other categorization schemes: Afterwards, we will list and comment on the available datasets, online gaze tracking services, and open source projects.
We will finish with our conclusions regarding the current state and future directions. Categorization and Structure of Visible Light Gaze Trackers The categorization of the works that we analyze in this paper is not trivial, because the borders between groups of methods are not always clear and in the literature different naming schemes exist.
In the early review by Morimoto and Mimica [ 5 ], methods using the eye appearance i.
Here, the given name refers to all the visible light methods and does not give information about the subcategories. Even in a more recent survey [ 6 ] where both infrared IR and visible light methods are considered, the latter group is considered as just an alternative, and its subcategories are left unclear.
Other categorization schemes also build on this ambiguity: With the aim of clearly identifying the borders between different visible light gaze estimation techniques and hopefully not adding to the confusionwe present a new categorization scheme: These methods only use the eye image pixel intensities to create a mapping to the gaze estimation.
The image pixels are converted to a vector representation via raster scanning and fed to the estimation component. Methods of this category also make use of a mapping to calculate the gaze; however, they use richer feature vectors compared to the methods in the previous category i.
Compared to the discriminative approach of the first two categories, the methods belonging to this category follow a generative approach by trying to model the eyes and maybe even the face.
The gaze is calculated geometrically using the model parameters. After explaining our categorization and the reasoning behind it, we can continue with the discussion about the software pipeline of these trackers. Although the variation in details is huge, a common skeletal structure that describes their software implementation can easily be identified as seen in Figure 1.The Audison AC Link can also be connected to control the amplifier as well as the AC Link and AD Link outputs, to expand the audio system with other Audison Voce amplifiers.
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