TouchTone: Interactive Local Image Adjustment Using Point-and-Swipe

Abstract

Recent proliferation of camera phones, photo sharing and social network services has significantly changed how we process our photos. Instead of going through the traditional download-edit-share cycle using desktop editors, an increasing number of photos are taken with camera phones and published through cellular networks. The immediacy of the sharing process means that on-device image editing, if needed, should be quick and intuitive. However, due to the limited computational resources and vastly different user interaction model on small screens, most traditional local selection methods can not be directly adapted to mobile devices. To address this issue, we present TouchTone, a new method for edge-aware image adjustment using simple finger gestures. Our method enables users to select regions within the image and adjust their corresponding photographic attributes simultaneously through a simple point-and-swipe interaction. To enable fast interaction, we develop a memory- and computation-efficient algorithm which samples a collection of 1D paths from the image, computes the adjustment solution along these paths, and interpolates the solutions to entire image through bilateral filtering. Our system is intuitive to use, and can support several local editing tasks, such as brightness, contrast, and color balance adjustments, within a minute on a mobile device.