{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/provenance-filtering-for-multimedia-phylogeny","title":"Provenance Filtering for Multimedia Phylogeny","arxiv_id":"1706.00447","date":"2017-06-01","proceeding":null,"authors":["Allan Pinto","Daniel Moreira","Aparna Bharati","Joel Brogan","Kevin Bowyer","Patrick Flynn","Walter Scheirer","Anderson Rocha"],"abstract":"Departing from traditional digital forensics modeling, which seeks to analyze\nsingle objects in isolation, multimedia phylogeny analyzes the evolutionary\nprocesses that influence digital objects and collections over time. One of its\nintegral pieces is provenance filtering, which consists of searching a\npotentially large pool of objects for the most related ones with respect to a\ngiven query, in terms of possible ancestors (donors or contributors) and\ndescendants. In this paper, we propose a two-tiered provenance filtering\napproach to find all the potential images that might have contributed to the\ncreation process of a given query $q$. In our solution, the first (coarse) tier\naims to find the most likely \"host\" images --- the major donor or background\n--- contributing to a composite/doctored image. The search is then refined in\nthe second tier, in which we search for more specific (potentially small) parts\nof the query that might have been extracted from other images and spliced into\nthe query image. Experimental results with a dataset containing more than a\nmillion images show that the two-tiered solution underpinned by the context of\nthe query is highly useful for solving this difficult task.","url_abs":"http://arxiv.org/abs/1706.00447v1","url_pdf":"http://arxiv.org/pdf/1706.00447v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"provenance-filtering-for-multimedia-phylogeny","repo_url":"https://gitlab.com/notredame-provenance/filtering","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}