Adaptive Photographic Composition Guidance

Jane L. E
Stanford University

Ohad Fried
Stanford University

Jingwan Lu
Adobe Research

Jianming Zhang
Adobe Research

Radomír Měch
Adobe Research

Jose Echevarria
Adobe Research

Pat Hanrahan
Stanford University

James A. Landay
Stanford University

Figure 1. To design our interactive composition guidance interface, we were interested in better understanding people's ability to recognize composition and to annotate them on a composition grid. Left to right: We collected annotations from both experienced photographers as well as novices on Mechanical Turk. Inspired by these results, we developed an algorithm for heuristically computing these lines, or adaptive armatures. We display these adaptive armatures as an overlay in an in-camera composition guidance tool and study how it impacts how people take photos.

Abstract

Photographic composition is often taught as alignment with composition grids—most commonly, the rule of thirds. Professional photographers use more complex grids, like the harmonic armature, to achieve more diverse dynamic compositions. We are interested in understanding whether these complex grids are helpful to amateurs. In a formative study, we found that overlaying the harmonic armature in the camera can help less experienced photographers discover and achieve different compositions, but it can also be overwhelming due to the large number of lines. Photographers actually use subsets of lines from the armature to explain different aspects of composition. However, this occurs mainly offline to analyze existing images. We propose bringing this mental model into the camera—by adaptively highlighting relevant lines to the current scene and point of view. We describe a saliency-based algorithm for selecting these lines and present an evaluation of the system that shows that photographers found the proposed adaptive armatures helpful for capturing more well-composed images.

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Bibtex

@inproceedings{e2020adaptive,
    title={Adaptive Photographic Composition Guidance},
    author={E, Jane L. and Fried, Ohad and Lu, Jingwan and Zhang, Jianming and M\v{e}ch, Radom\'{\i}r and Echevarria, Jose and Hanrahan, Pat and Landay, James A.},
    booktitle={Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems},
    url = {https://dl.acm.org/doi/10.1145/3313831.3376635},
    doi = {10.1145/3313831.3376635},
    pages={1--13},
    year={2020},
    organization={ACM},
    series = {CHI ’20}
}