Audiovisual Zooming: What You See Is What You Hear

When capturing videos on a mobile platform, often the target of interest is contaminated by the surrounding environment. To alleviate the visual irrelevance, camera panning and zooming provide the means to isolate a desired field of view (FOV). However, the captured audio is still contaminated by signals outside the FOV. This effect is unnatural---for human perception, visual and auditory cues must go hand-in-hand. We present the concept ofAudiovisual Zooming, whereby an auditory FOV is formed to match the visual. Our framework is built around the classic idea of beamforming, a computational approach to enhancing sound from a single direction using a microphone array. Yet, beamforming on its own can not incorporate the auditory FOV, as the FOV may include an arbitrary number of directional sources. We formulate our audiovisual zooming as a generalized eigenvalue problem and propose an algorithm for efficient computation on mobile platforms. To inform the algorithmic and physical implementation, we offer a theoretical analysis of our algorithmic components as well as numerical studies for understanding various design choices of microphone arrays. Finally, we demonstrate audiovisual zooming on two different mobile platforms: a mobile smartphone and a 360$^\circ $ spherical imaging system for video conference settings.