Building the Internet of Behaviors (IOB) obviously requires capturing human behavior. Sensor input from eye tracking has been widely used for profiling in market research, adaptive user interfaces, and other smart systems, but requires dedicated hardware. The wide spread of webcams in consumer devices like phones, notebooks, and smart TVs has fostered eye tracking with commodity cameras. In this paper, we present a systematic review across the IEEE and ACM databases – complemented by snowballing and input from eye tracking experts at CHI 2021 – to list and characterize publicly available software for webcam eye tracking that estimate the point-ofregard with no additional hardware. Information from articles was supplemented by searching author websites and code repositories, and contacting authors. 16 eye trackers were found that can be used. The restrictions regarding license terms and technical performance are presented, enabling developers to choose an appropriate software for their IoB application.
https://scholarspace.manoa.hawaii.e.../0169fe63-b583-4df4-9365-c6e8df04ea11/content
The post Webcam Eye Tracking for Desktop and Mobile Devices: A Systematic Review appeared first on GazeRecorder.
https://scholarspace.manoa.hawaii.e.../0169fe63-b583-4df4-9365-c6e8df04ea11/content
The post Webcam Eye Tracking for Desktop and Mobile Devices: A Systematic Review appeared first on GazeRecorder.