Gaze-based interaction for semi-automatic photo cropping

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. Author Keywords cropping, photography, composition, evaluation, eye tracking, visual perception ACM Classification Keywords H5.2. Information interfaces and presentation: User Interfaces.

• Type: Conference
• Year: 2006
• Where: CHI
• Authors: Anthony Santella, Maneesh Agrawala, Douglas DeCarlo, David Salesin, Michael F. Cohen
• Keywords: ACM Classification Keywords, Automatic Crops, Automatic Snapshot Recomposition, CHI 2006, Human Computer Interaction