GSET somi
Hamed Ahmadi, Saman Zad Tootaghaj, Sajad Mowlaei, Mahmoud Reza Hashemi, Shervin Shirmohammadi · 2016
In this paper, we present an eye tracking dataset of computer game players who played the side-scrolling cloud game Somi. The game was streamed in the form of video from the cloud to the player. This dataset can be used for designing and testing game-specific visual attention models. The source code of the game is also available to facilitate further modifications and adjustments. For collecting this data, male and female candidates were asked to play the game in front of a remote eye-tracking device. For each player, we recorded gaze points, video frames of the gameplay, and mouse and keyboard commands. For each video frame, a list of its game objects with their locations and sizes was also recorded. This data, synchronized with eye-tracking data, allows one to calculate the amount of attention that each object or group of objects draw from each player. As a benchmark, we also show various attention patterns could be identified among players.