{"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/real-time-6dof-pose-relocalization-for-event","title":"Real-Time 6DOF Pose Relocalization for Event Cameras with Stacked Spatial LSTM Networks","arxiv_id":"1708.09011","date":"2017-08-22","proceeding":null,"authors":["Anh Nguyen","Thanh-Toan Do","Darwin G. Caldwell","Nikos G. Tsagarakis"],"abstract":"We present a new method to relocalize the 6DOF pose of an event camera solely\nbased on the event stream. Our method first creates the event image from a list\nof events that occurs in a very short time interval, then a Stacked Spatial\nLSTM Network (SP-LSTM) is used to learn the camera pose. Our SP-LSTM is\ncomposed of a CNN to learn deep features from the event images and a stack of\nLSTM to learn spatial dependencies in the image feature space. We show that the\nspatial dependency plays an important role in the relocalization task and the\nSP-LSTM can effectively learn this information. The experimental results on a\npublicly available dataset show that our approach generalizes well and\noutperforms recent methods by a substantial margin. Overall, our proposed\nmethod reduces by approx. 6 times the position error and 3 times the\norientation error compared to the current state of the art. The source code and\ntrained models will be released.","url_abs":"http://arxiv.org/abs/1708.09011v3","url_pdf":"http://arxiv.org/pdf/1708.09011v3.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":"real-time-6dof-pose-relocalization-for-event","repo_url":"https://github.com/nqanh/pose_relocalization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"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}