English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The contextual information (i.e., the time and location) in which a photo istaken can be easily tampered with or falsely claimed by forgers to achievemalicious purposes, e.g., creating fear among the general public. A rich bodyof work has focused on detecting photo tampering and manipulation by verifyingthe integrity of image content. Instead, we aim to detect photo misuse byverifying the capture time and location of photos. This paper is motivated bythe law of nature that sun position varies with the time and location, whichcan be used to determine whether the claimed contextual information correspondswith the sun position that the image content actually indicates. Priorapproaches to inferring sun position from images mainly rely on vanishingpoints associated with at least two shadows, while we propose novel algorithmswhich utilize only one shadow in the image to infer the sun position.Meanwhile, we compute the sun position by applying astronomical algorithmswhich take as input the claimed capture time and location. Only when the twoestimated sun positions are consistent can the claimed contextual informationbe genuine. We have developed a prototype called IMAGEGUARD. The experimentalresults show that our method can successfully estimate sun position and detectthe time-location inconsistency with high accuracy. By setting the thresholdsto be 9.4 degrees and 5 degrees for the sun position distance and the altitudeangle distance, respectively, our system can correctly identify 91.5% offalsified photos with fake contextual information.

Validating the Contextual Information of Outdoor Images for Photo Misuse Detection