Dataset: 4DLFVD - A 4D LIGHT FIELD VIDEO DATASET
We present a 4D Light Field (LF) video dataset collected by the camera matrix, to be used for designing and testing algorithms and systems for LF video coding and processing. For collecting these videos, a 10x10 LF capture matrix composed of 100 cameras is designed and implemented, and the resolution of each camera is 1920x1056. The videos are taken in real and varying illumination conditions. The dataset contains a total of nine groups of LF videos, of which eight groups are collected with a fixed camera matrix position and a fixed orientation. The last group was collected by rotating around an outdoor specific target. Each group of LF videos consists of 100 video streams, which are encoded by H.265. Both static scenes (indoor potted plants and furniture, etc.) and dynamic scenes (roadside vehicles and pedestrians, etc.) are included, which can increase the diversity of our dataset. As a benchmark, we present the results of a depth estimation method designed by ourselves, and show that our dataset can be used for further processing and applications, such as objection detection and 3D modeling.
You can download the dataset for free from IEEE DataPort (you will need to create a free IEEE account, if you are not an IEEE member already). Click here for more details about this dataset.
Dataset: YawDD
A dataset of videos, recorded by an in-car camera, of drivers in an actual car with various facial characteristics (male and female, with and without glasses/sunglasses, different ethnicities) talking, singing, being silent, and yawning. It can be used primarily to develop and test algorithms and models for yawning detection, but also recognition and tracking of face and mouth. The videos are taken in natural and varying illumination conditions.
You can download the dataset for free from IEEE DataPort (you will need to create a free IEEE account, if you are not an IEEE member already). Click here for more details about this dataset.
Dataset: FooDD
Images of various foods, taken with different cameras and different lighting conditions. Images can be used to design and test Computer Vision techniques that can recognize foods and estimate their calories and nutrition.
You can download the dataset for free from IEEE DataPort (you will need to create a free IEEE account, if you are not an IEEE member already). Click here for more details about this dataset.
Dataset: GSET Somi
This is an eye tracking dataset of 84 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. The dataset consists of 135 raw videos (YUV) at 720p and 30 fps with eye tracking data for both eyes (left and right). 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. This dataset can be used for designing and testing game-specific visual attention models.
You can download the dataset for free from IEEE DataPort (you will need to create a free IEEE account, if you are not an IEEE member already). Click here for more details about this dataset.
Dataset: FOCUS
EEG brain recordings of ADHD and non-ADHD individuals during gameplay of a brain controlled game, recorded with an EMOTIV EEG headset. It can be used to design and test machine learning methods to detect individuals with ADHD.
You can download the dataset for free from IEEE DataPort (you will need to create a free IEEE account, if you are not an IEEE member already). Click here for more details about this dataset.
Software: An Open Source Cloud Gaming Testbed Using DirectShow
An open source cloud gaming testbed the screen capturing module of which is fundamentally a DirectShow filter and, hence, can be tuned for any DirectShow compatible video game. It also facilitates the measurement of delay and video quality.
See here for more details.