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ABSTRACT

We propose a system for automatically detecting the ways in which images have been copied and edited or manipulated. We draw upon these manipulation cues to construct probable parent-child relationships between pairs of images, where the child image was derived through a series of visual manipulations on the parent image. Through the detection of these relationships across a plurality of images, we can construct a history of the image, called the visual migration map (VMM), which traces the manipulations applied to the image through past generations. We propose to apply VMMs as part of a larger internet image archaeology system (IIAS), which can process a given set of related images and surface many interesting instances of images from within the set. In particular, the image closest to the "original" photograph might be among the images with the most descendants in the VMM. Or, the images that are most deeply descended from the original may exhibit unique differences and changes in the perspective being conveyed by the author. We evaluate the system across a set of photographs crawled from the web and find that many types of image manipulations can be automatically detected and used to construct plausible VMMs. These maps can then be successfully mined to find interesting instances of images and to suppress uninteresting or redundant ones, leading to a better understanding of how images are used over different times, sources, and contexts.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.m MISCELLANEOUS

General Terms:
Algorithms, Experimentation

Keywords:
image manipulation history, internet image mining, perspective discovery