ZoomShop: Depth-Aware Editing of Photographic Composition

Sean J. Liu, Maneesh Agrawala, Stephen DiVerdi and Aaron Hertzmann
EUROGRAPHICS 2022, the 43nd Annual Conference of the European Association for Computer Graphics, 2022
We present ZoomShop, a photographic composition editing tool for adjusting relative size, position, and foreshortening of scene elements. Given an image and corresponding depth map as input, ZoomShop combines a novel non-linear camera model and a depth-aware image warp to reproject and deform the image. Users can isolate objects by selecting depth ranges and adjust their scale and foreshortening, which controls the paths of the camera rays through the scene. Users can also select 2D image regions and translate them, which determines the objective function in the image warp optimization. We demonstrate that ZoomShop can be used to achieve useful compositional goals, such as making a distant object more prominent while preserving foreground scenery, or making objects both larger and closer together so they still fit in the frame.

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