Gaze-Based Interaction for Semi-Automatic Photo Cropping
Anthony Santella, Maneesh Agrawala, Doug DeCarlo, David Salesin, Michael Cohen
Abstract
We present an interactive method for cropping photographs given minimal
information about the location of important content, provided by eye
tracking. Cropping is formulated in a general optimization framework that
facilitates adding new composition rules, as well as adapting the system to
particular applications. Our system uses fixation data to identify important
content and compute the best crop for any given aspect ratio or size,
enabling applications such as automatic snapshot recomposition, adaptive
documents, and thumbnailing. We validate our approach with studies in which
users compare our crops to ones produced by hand and by a completely
automatic approach. Experiments show that viewers prefer our gaze-based
crops to uncropped images and fully automatic crops.
Original well-composed images (left), adapted to two different aspect ratios using our gaze-based approach. An ADL document (right) using our crops. If eye movements are collected passively during document construction, our approach allows adaptation of images to arbitrary aspect ratios with no explicit user effort.