1 to 10 of 20 Results
Mar 3, 2025 - Collaborative Artificial Intelligence
Sood, Ekta; Kögel, Fabian; Bulling, Andreas, 2024, "VQA-MHUG", https://doi.org/10.18419/DARUS-4428, DaRUS, V2
We present VQA-MHUG - a novel 49-participant dataset of multimodal human gaze on both images and questions during visual question answering (VQA), collected using a high-speed eye tracker. To the best of our knowledge, this is the first resource containing multimodal human gaze data over a textual question and the corresponding image. Our corpus en... |
May 16, 2024 - Collaborative Artificial Intelligence
Bulling, Andreas, 2024, "InvisibleEye", https://doi.org/10.18419/DARUS-3288, DaRUS, V1
We recorded a dataset of more than 280,000 close-up eye images with ground truth annotation of the gaze location. A total of 17 participants were recorded, covering a wide range of appearances: Gender: Five (29%) female and 12 (71%) male Nationality: Seven (41%) German, seven (41%) Indian, one (6%) Bangladeshi, one (6%) Iranian, and one (6%) Greek... |
Apr 8, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "VisRecall++: Analysing and Predicting Recallability of Information Visualisations from Gaze Behaviour (Dataset and Reproduction Data)", https://doi.org/10.18419/DARUS-3138, DaRUS, V1, UNF:6:NwphGtoYrBQqd2TyRh0OHA== [fileUNF]
This dataset contains stimuli and collected participant data of VisRecall++. The structure of the dataset is described in the README-File. Further, if you are interested in related codes of the publication, you can find a copy of the code repository (see Metadata for Research Software) within this dataset. |
Mar 22, 2024 - SFB-TRR 161 A07 "Visual Attention Modeling for Optimization of Information Visualizations"
Wang, Yao; Bulling, Andreas, 2024, "Saliency3D: A 3D Saliency Dataset Collected on Screen (Dataset and Experiment Application)", https://doi.org/10.18419/DARUS-4101, DaRUS, V1
While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. Our experimental design reduces the cost and complexity of 3D saliency... |
Mar 14, 2023 - Collaborative Artificial Intelligence
Bulling, Andreas, 2023, "MPIIFaceGaze", https://doi.org/10.18419/DARUS-3240, DaRUS, V1
We present the MPIIFaceGaze dataset which is based on the MPIIGaze dataset, with the additional human facial landmark annotation and the face regions available. We added additional facial landmark and pupil center annotations for 37,667 face images. Facial landmarks annotations were conducted in a semi-automatic manner as running facial landmark de... |
Mar 8, 2023 - Collaborative Artificial Intelligence
Bulling, Andreas, 2023, "Labeled pupils in the wild (LPW)", https://doi.org/10.18419/DARUS-3237, DaRUS, V1
We present labelled pupils in the wild (LPW), a novel dataset of 66 high-quality, high-speed eye region videos for the development and evaluation of pupil detection algorithms. The videos in our dataset were recorded from 22 participants in everyday locations at about 95 FPS using a state-of-the-art dark-pupil head-mounted eye tracker. They cover p... |
Feb 24, 2023 - Collaborative Artificial Intelligence
Bulling, Andreas, 2023, "MPIIEmo", https://doi.org/10.18419/DARUS-3287, DaRUS, V1
We present a human-validated dataset that contains 224 high-resolution, multi-view video clips and audio recordings of emotionally charged interactions between eight couples of actors. The dataset is fully annotated with categorical labels for four basic emotions (anger, happiness, sadness, and surprise) and continuous labels for valence, activatio... |
Nov 30, 2022 - Collaborative Artificial Intelligence
Bulling, Andreas, 2022, "DEyeAdicContact", https://doi.org/10.18419/DARUS-3289, DaRUS, V1, UNF:6:7QxaU+oeOPfaI8gMpCn5cw== [fileUNF]
We created our own dataset of natural dyadic interactions with fine-grained eye contact annotations using videos of dyadic interviews published on YouTube. Especially compared to lab-based recordings, these Youtube interviews allow us to analyse behaviour in a natural situation. All interviews were conducted via video conferencing and provide front... |
Nov 30, 2022 - Collaborative Artificial Intelligence
Bulling, Andreas, 2022, "MPIIMobileAttention", https://doi.org/10.18419/DARUS-3285, DaRUS, V1
This is a novel long-term dataset of everyday mobile phone interactions, continuously recorded from 20 participants engaged in common activities on a university campus over 4.5 hours each (more than 90 hours in total). |
Nov 30, 2022 - Collaborative Artificial Intelligence
Bulling, Andreas, 2022, "MPIIPrivacEye", https://doi.org/10.18419/DARUS-3286, DaRUS, V1
First-person video dataset recorded in daily life situations of 17 participants, annotated by themselves for privacy sensitivity. The dataset of Steil et al. contains more than 90 hours of data recorded continuously from 20 participants (six females, aged 22-31) over more than four hours each. Participants were students with different backgrounds a... |
