{"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/making-a-long-story-short-a-multi-importance","title":"Making a long story short: A Multi-Importance fast-forwarding egocentric videos with the emphasis on relevant objects","arxiv_id":"1711.03473","date":"2017-11-09","proceeding":null,"authors":["Michel Melo Silva","Washington Luis Souza Ramos","Felipe Cadar Chamone","João Pedro Klock Ferreira","Mario Fernando Montenegro Campos","Erickson Rangel Nascimento"],"abstract":"The emergence of low-cost high-quality personal wearable cameras combined\nwith the increasing storage capacity of video-sharing websites have evoked a\ngrowing interest in first-person videos, since most videos are composed of\nlong-running unedited streams which are usually tedious and unpleasant to\nwatch. State-of-the-art semantic fast-forward methods currently face the\nchallenge of providing an adequate balance between smoothness in visual flow\nand the emphasis on the relevant parts. In this work, we present the\nMulti-Importance Fast-Forward (MIFF), a fully automatic methodology to\nfast-forward egocentric videos facing these challenges. The dilemma of defining\nwhat is the semantic information of a video is addressed by a learning process\nbased on the preferences of the user. Results show that the proposed method\nkeeps over $3$ times more semantic content than the state-of-the-art\nfast-forward. Finally, we discuss the need of a particular video stabilization\ntechnique for fast-forward egocentric videos.","url_abs":"http://arxiv.org/abs/1711.03473v3","url_pdf":"http://arxiv.org/pdf/1711.03473v3.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":"making-a-long-story-short-a-multi-importance","repo_url":"https://github.com/verlab/SemanticFastForward_JVCI_2018","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"making-a-long-story-short-a-multi-importance","repo_url":"https://github.com/verlab/SemanticFastForward_CVPR_2018","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"making-a-long-story-short-a-multi-importance","repo_url":"https://github.com/verlab/SemanticFastForward_TPAMI_2020","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"video-stabilization","task_name":"Video Stabilization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}