{"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/co-fusion-real-time-segmentation-tracking-and","title":"Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple Objects","arxiv_id":"1706.06629","date":"2017-06-20","proceeding":null,"authors":["Martin Rünz","Lourdes Agapito"],"abstract":"In this paper we introduce Co-Fusion, a dense SLAM system that takes a live\nstream of RGB-D images as input and segments the scene into different objects\n(using either motion or semantic cues) while simultaneously tracking and\nreconstructing their 3D shape in real time. We use a multiple model fitting\napproach where each object can move independently from the background and still\nbe effectively tracked and its shape fused over time using only the information\nfrom pixels associated with that object label. Previous attempts to deal with\ndynamic scenes have typically considered moving regions as outliers, and\nconsequently do not model their shape or track their motion over time. In\ncontrast, we enable the robot to maintain 3D models for each of the segmented\nobjects and to improve them over time through fusion. As a result, our system\ncan enable a robot to maintain a scene description at the object level which\nhas the potential to allow interactions with its working environment; even in\nthe case of dynamic scenes.","url_abs":"http://arxiv.org/abs/1706.06629v1","url_pdf":"http://arxiv.org/pdf/1706.06629v1.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":"co-fusion-real-time-segmentation-tracking-and","repo_url":"https://github.com/martinruenz/co-fusion","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"instance-segmentation","task_name":"Instance Segmentation"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-slam","task_name":"Object SLAM"},{"task_slug":"semantic-slam","task_name":"Semantic SLAM"},{"task_slug":"simultaneous-localization-and-mapping","task_name":"Simultaneous Localization and Mapping"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1706.06629","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}