Audible Panorama: Automatic Spatial Audio Generation for Panorama Imagery (CHI 2019)

Audible Panorama:Automatic SpatialAudio GenerationforPanorama Imagery Haikun Huang*, University of Massachusetts, Boston Michael Solah*, University of Massachusetts, Boston Dingzeyu Li, Adobe Research/University of Columbia University Lap-Fai Yu, George Mason University 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.