English

Audiovisual Database with 360 Video and Higher-Order Ambisonics Audio for Perception, Cognition, Behavior, and QoE Evaluation Research

Image and Video Processing 2022-12-29 v1 Multimedia Sound Audio and Speech Processing

Abstract

Research into multi-modal perception, human cognition, behavior, and attention can benefit from high-fidelity content that may recreate real-life-like scenes when rendered on head-mounted displays. Moreover, aspects of audiovisual perception, cognitive processes, and behavior may complement questionnaire-based Quality of Experience (QoE) evaluation of interactive virtual environments. Currently, there is a lack of high-quality open-source audiovisual databases that can be used to evaluate such aspects or systems capable of reproducing high-quality content. With this paper, we provide a publicly available audiovisual database consisting of twelve scenes capturing real-life nature and urban environments with a video resolution of 7680x3840 at 60 frames-per-second and with 4th-order Ambisonics audio. These 360 video sequences, with an average duration of 60 seconds, represent real-life settings for systematically evaluating various dimensions of uni-/multi-modal perception, cognition, behavior, and QoE. The paper provides details of the scene requirements, recording approach, and scene descriptions. The database provides high-quality reference material with a balanced focus on auditory and visual sensory information. The database will be continuously updated with additional scenes and further metadata such as human ratings and saliency information.

Keywords

Cite

@article{arxiv.2212.13442,
  title  = {Audiovisual Database with 360 Video and Higher-Order Ambisonics Audio for Perception, Cognition, Behavior, and QoE Evaluation Research},
  author = {Thomas Robotham and Ashutosh Singla and Olli S. Rummukainen and Alexander Raake and Emanuël A. P. Habets},
  journal= {arXiv preprint arXiv:2212.13442},
  year   = {2022}
}

Comments

6 pages, 2 figures, accepted and presented at the 2022 14th International Conference on Quality of Multimedia Experience (QoMEX). Database is publicly accessible at https://qoevave.github.io/database/