©2017 by Haikun (Quincy) Huang.

Audible Panorama:Automatic SpatialAudio GenerationforPanorama Imagery

Haikun Huang*, Michael Solah*, Dingzeyu LiLap-Fai Yu

*The two authors contributed equally to this paper.

Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2019)​​

Abstract

As 360° cameras and virtual reality headsets become more popular, panorama images have become increasingly ubiquitous. While sounds are essential in delivering immersive and interactive user experiences, most panorama images, however, do not come with native audio. In this paper, we propose an automatic algorithm to augment static panorama images through realistic audio assignment. We accomplish this goal through object detection, scene classification, object depth estimation, and audio source placement. We built an audio file database composed of over 500 audio files to facilitate this process.
We designed and conducted a user study to verify the efficacy of various components in our pipeline. We run our method on a large variety of panorama images of indoor and outdoor scenes. By analyzing the statistics, we learned the relative importance of these components, which can be used in prioritizing for power-sensitive time-critical tasks like mobile augmented reality (AR) applications.

Acknowledgments

We are grateful to the anonymous reviewers for their useful
comments and suggestions. We would also like to thank the
user study participants, and we are also thankful for the free
audio fles from freesound.org. The authors would also like to
thank all the Flickr users for sharing their panorama images.
This research project is supported by the National Science
Foundation under award number 1565978.

 

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