ISMAR_PointCloud_EyeTracking

The official repo for QAVA-DPC: Eye-Tracking Based Quality Assessment and Visual Attention Dataset for Dynamic Point Cloud in 6 DoF ISMAR 2023

Visual Saliency Map

Generated visual saliency map per user can be downloaded via this link: Visual Saliancy Map
Name Convension of files: 001_A: uer_session
H1_C2_R2_191: stimuli name_codec_distortion level_rotation_degree
4246452_rafa_084.txt filename explanation: timestamp_point cloud name_frame_number

Raw Gaze data for 40 users

In this folder, it includes all the experimental data related to the eye-tracking (in the json file) and the original opinion scores (in two txt files) of each user. It can be downloaded from: GazeData
user_001 : user_userindex 001_A.txt: userindex_session.txt
20230317-2301_001_A.json:date_userindex_session.json

Visualization:

This is the video of the H5_C0_R0_BackView

and H5_C0_R0_FrontView.

Conditions of use

If you wish to use any of the provided material in your research, we kindly ask you to cite our paper.

• BibTex

@INPROCEEDINGS{10316522,
  author={Zhou, Xuemei and Viola, Irene and Alexiou, Evangelos and Jansen, Jack and Cesar, Pablo},
  booktitle={2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}, 
  title={QAVA-DPC: Eye-Tracking Based Quality Assessment and Visual Attention Dataset for Dynamic Point Cloud in 6 DoF}, 
  year={2023},
  volume={},
  number={},
  pages={69-78},
  keywords={Point cloud compression;Measurement;Visualization;Solid modeling;Head-mounted displays;Gaze tracking;Inspection;Volumetric video;Dynamic point cloud;Visual saliency;Visual attention;Subjective quality assessment;Objective quality metrics;Eye tracking;6DoF},
  doi={10.1109/ISMAR59233.2023.00021}}

About

The QAVA-DPC Dataset is maintained by the Distributed & Interactive Systems (DIS) research group at Centrum Wiskunde & Informatica (CWI).

Contact the authors

• Xuemei Zhou: xuemei.zhou@cwi.nl