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In-Vehicle Gaze Estimation DataSet

We provide an in-vehicle gaze estimation dataset IVGaze.

  • IVGaze contains 44,705 images of 125 subjects. We divide the dataset into three subsets based on subjects. The image numbers of the three subsets are 15,165, 14,674, and 14,866. Three-fold cross-validation should be performed on the dataset.

  • The dataset was collected between 9 am and 7 pm in outdoor environments, covering a wide range of lighting conditions.

  • We consider two face accessories during the collection: glasses and masks. We also required a few subjects to wear sunglasses to facilitate future research.

Dataset Structure

IVGazeDataset
├── class.label
├── Norm
│   ├── 20220811
│   │   ├── subject0000_out_eye_mask
│   │   │    ├── 1.jpg
│   │   │    ├── ...
│   │   │    ├── ...
│   │   │    ├── 81.jpg
│   │   ├── ...
│   │   ├── ...
│   │   ├── subject0000_out_eye_nomask
│   ├── 20221009
│   ├── 20221010
│   ├── 20221011
│   ├── 20221012
│   ├── 20221013
│   ├── 20221014
│   ├── 20221017
│   ├── 20221018
│   ├── 20221019
│   ├── 20221020
│   └── label_class
│       ├── train1.txt
│       ├── train2.txt
│       └── train3.txt
└── Origin
    ├── 20220811
    ├── ...
    ├── ...
    ├── 20221020
    └── label_class
        ├── train1.txt
        ├── train2.txt
        └── train3.txt
  • class.label: This section offers gaze zone classification details. The first row denotes the class number according to label_class. The second row represents the original numbers assigned during the data collection phase. The third row indicates coarse region numbers.
  • Norm: This section contains normalized images and their corresponding labels.
  • Norm/label_class: Here, you'll find label files for three-fold validation.
  • Origin: This section provides original images directly cropped from facial images, along with their label files.

Usage

To retrieve data from the IVGaze Dataset, begin by reading the label file, such as Norm/label_class/train1.txt. Each line in the label file is formatted with space-separated values. You can read one line at a time for processing.

root = 'IVGazeDataset/Norm'
with open(os.path.join(root, 'label_class/train1.txt')) as infile:
    lines = infile.readlines()

for line in lines:
    line = line.strip().split(' ')

    # Read the image
    image_name = line[0]
    image = cv2.imread(os.path.join(root, image_name))

    # GT for gaze and zone
    gaze = np.fromstring(line[1], sep=',')
    zone = int(line[3])

Download

To obtain access to the dataset, please send an email to y.cheng.2@bham.ac.uk. You will receive a Google Drive link within three days for downloading the dataset.

Here's the email prompt for requesting access to the IVGaze Dataset. Please do not change the email subject.

Subject: Request for Access to IVGaze Dataset

Dear Yihua,

I hope this email finds you well.

I am writing to request access to the IVGaze Dataset. My name is [Your Name], and I am a [student/researcher] from [Your Affiliation].

I assure you that I will only utilize the dataset for academic and research purposes and will not use it for commercial activities.

Thank you for considering my request. I look forward to receiving access to the dataset.

Best regards,
[Your Name]