{"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/fast-forward-video-based-on-semantic","title":"Fast-Forward Video Based on Semantic Extraction","arxiv_id":"1708.04160","date":"2017-08-14","proceeding":null,"authors":["Washington Luis Souza Ramos","Michel Melo Silva","Mario Fernando Montenegro Campos","Erickson Rangel Nascimento"],"abstract":"Thanks to the low operational cost and large storage capacity of smartphones\nand wearable devices, people are recording many hours of daily activities,\nsport actions and home videos. These videos, also known as egocentric videos,\nare generally long-running streams with unedited content, which make them\nboring and visually unpalatable, bringing up the challenge to make egocentric\nvideos more appealing. In this work we propose a novel methodology to compose\nthe new fast-forward video by selecting frames based on semantic information\nextracted from images. The experiments show that our approach outperforms the\nstate-of-the-art as far as semantic information is concerned and that it is\nalso able to produce videos that are more pleasant to be watched.","url_abs":"http://arxiv.org/abs/1708.04160v3","url_pdf":"http://arxiv.org/pdf/1708.04160v3.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":"fast-forward-video-based-on-semantic","repo_url":"https://github.com/verlab/SemanticFastForward_ICIP_2016","is_official":1,"mentioned_in_paper":0,"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}