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Tatt-E is a large-scale sequestered evaluation of tattoo recognition algorithms to support operationally relevant use cases, including tattoo identification, region of interest, tattoo detection/localization, and clustering. For more information, please visit the Tatt-E Homepage.
Based on the outcomes of the Tatt-C activity, tattoo recognition algorithm accuracy is often influenced by the consistency and quality of the tattoo images. Tatt-BP provides best practice recommendations and guidelines for the proper collection of tattoo images to support image-based tattoo recognition. Tatt-BP materials are available on the Tatt-BP Homepage.
The goal of the Tattoo Recognition Technology – Challenge (Tatt-C) was to advance research and development into automated image-based tattoo recognition technology. The challenge focused on tattoo matching and retrieval from still images captured operationally by law enforcement agencies. Tatt-C activity culminated with a workshop and a final report with outcomes and recommendations. The Tatt-C dataset is available on an ongoing basis for interested researchers. For more information, please visit the Tatt-C Homepage.