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    "abbrevTitle": "SMPTE Mot. Imag. J",
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    "abstract": "We present a deep learning-based algorithm that can automatically rotoscope people in a given scene, without any user input. Current approaches to image matting require a significant amount of human input, irrespective of whether it is manually rotoscoped or through a chroma key. This study shows that this algorithm can perform as well as and even surpass the rotoscoping capabilities of the Adobe After Effects’ RotoBrush tool, in a variety of scenes comprising different lighting conditions, movements, and subjects. This makes it suitable for integration within a visual effects (VFX) pipeline.",
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    "authors": [
      {
        "bio": "Oscar Estrada Torrejonis a recent graduate from the Motion Picture Science Program at the Rochester Institute of Technology (RIT), Rochester, NY. His interests include content development for digital platforms, post-production technology, and visual effects. His experience includes creating content marketing videos for his university, as well as managing broadcast equipment and post-production workflows on board oceanographic research vessels. Torrejon graduated Summa Cum Laude in 2019 and received the Outstanding Undergraduate Scholar Award and the Outstanding International Student Service Award for his service to his alma matter.",
        "name": "Oscar Estrada Torrejon",
        "orcid": "0000-0003-0911-6803"
      },
      {
        "bio": "Nicholas Perettirecently graduated from the Rochester Institute of Technology (RIT), Rochester, NY, with a major in software engineering and a minor in imaging science. While at RIT, he worked for one year at Apple Inc., Cupertino, CA, beginning with the Photography Group and then spent six months with the Computer Vision and Machine Learning Team. He is currently the head of machine learning at Scythe Robotics based in Boulder, CO, which is creating a self-driving lawn mower for golf courses and municipalities. Peretti enjoys basketball and snowboarding, when not interacting with a computer.",
        "name": "Nicholas Peretti"
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      {
        "bio": "Ricardo Figueroais currently an associate professor, the program director for the Motion Picture Science Program, and an interim co-director of the School of Film and Animation, Rochester Institute of Technology (RIT), Rochester, NY. Figueroa joined RIT after working at Eastman Kodak, Rochester, for ten years, where he held positions as film and digital lab manager, digital/hybrid technologies regional director, digital imaging research engineer, and Kodak operating system manager. Figueroa holds a BSEE and an MSEE from the University of Puerto Rico, Mayagüez, Puerto Rico, and is currently pursuing a PhD in computing and information sciences at RIT. His research interests are in the areas of machine learning and deep learning for image processing applications. Outside of work, Figueroa is an avid triathlete, soccer player, and golfer. He is also active in various professional and civic organizations.",
        "name": "Ricardo Figueroa",
        "orcid": "0000-0002-6298-9737"
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      "year": "2019",
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    "docLabel": "SMPTE Motion Imaging Journal ( Volume: 129, Issue: 2, March 2020)",
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    "docTitle": "Rotoscope Automation with Deep Learning",
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    "keywords": [
      "Compositing",
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