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[1606.05814] Eye Tracking for Everyone
Source: arxiv.org
Article summary:
1. GazeCapture is the first large-scale dataset for eye tracking, containing data from over 1450 people consisting of almost 2.5M frames.
2. iTracker, a convolutional neural network for eye tracking, is trained using GazeCapture and achieves a significant reduction in error over previous approaches while running in real time (10-15fps) on a modern mobile device.
3. The features learned by iTracker generalize well to other datasets, achieving state-of-the-art results.
Article analysis:
The article “Eye Tracking for Everyone” presents an innovative approach to eye tracking technology that can be used on commodity hardware such as mobile phones and tablets without the need for additional sensors or devices. The article provides evidence of the effectiveness of this approach through the introduction of GazeCapture, a large-scale dataset for eye tracking, and iTracker, a convolutional neural network for eye tracking which has achieved a significant reduction in error over previous approaches while running in real time (10-15fps) on a modern mobile device. The article also claims that the features learned by iTracker generalize well to other datasets, achieving state-of-the-art results.
The trustworthiness and reliability of this article can be assessed by looking at its potential biases and their sources, one-sided reporting, unsupported claims, missing points of consideration, missing evidence for the claims made, unexplored counterarguments, promotional content, partiality etc. In terms of potential biases and their sources it appears that there are none present in this article as it does not appear to be promoting any particular product or service nor does it appear to have any political or ideological agenda behind it. Furthermore there is no one sided reporting as both sides of the argument are presented equally with evidence provided to support each side's claim. There are also no unsupported claims as all claims made are backed up with evidence from experiments conducted using GazeCapture and iTracker as well as other datasets which have achieved state-of-the art results when using these tools. Additionally there are no missing points of consideration or missing evidence for the claims made as all relevant information is provided within the article itself along with references to external sources where further information can be found if needed. Finally there are no unexplored counterarguments or promotional content present in this article making it an overall reliable source of information regarding eye tracking technology and its applications on commodity hardware such as mobile phones and tablets without additional sensors or devices being required.