DeclutterCam: A Photographic Assistant System with Clutter Detection and Removal

TL;DR

DeclutterCam is an AI-powered photographic assistant that detects and removes visual clutter in photos, helping beginners and experts create clearer, story-focused images through interactive tools and real-time feedback.

Contribution

The system introduces novel AI algorithms and user interactions for clutter detection and removal, enhancing photographic storytelling and user experience.

Findings

Beginners produced higher-quality, less cluttered photos.

Users could explore more photographic ideas with real-time feedback.

Experts confirmed improved photo quality and storytelling clarity.

Abstract

Photographs convey the stories of photographers to the audience. However, this story-telling aspect of photography is easily distracted by visual clutter. Informed by a pilot study, we identified the kinds of clutter that amateurs frequently include in their photos. We were thus inspired to develop DeclutterCam, a photographic assistant system that incorporates novel user interactions and AI algorithms for photographic decluttering. Clutter elements are detected by an aesthetic quality evaluation algorithm and are highlighted so that users can interactively identify distracting elements. A GAN-based iterative clutter removal tool enables users to test their photographic ideas in real-time. User studies with 32 photography beginners demonstrate that our system provides flexible interfaces, accurate algorithms, and immediate feedback that allow users to avoid clutter and explore more photographic ideas. Evaluations by photography experts show that users can take higher-quality photos that better convey the intended story using our system.