{"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/mlpnp-a-real-time-maximum-likelihood-solution","title":"MLPnP - A Real-Time Maximum Likelihood Solution to the Perspective-n-Point Problem","arxiv_id":"1607.08112","date":"2016-07-27","proceeding":null,"authors":["Steffen Urban","Jens Leitloff","Stefan Hinz"],"abstract":"In this paper, a statistically optimal solution to the Perspective-n-Point\n(PnP) problem is presented. Many solutions to the PnP problem are geometrically\noptimal, but do not consider the uncertainties of the observations. In\naddition, it would be desirable to have an internal estimation of the accuracy\nof the estimated rotation and translation parameters of the camera pose. Thus,\nwe propose a novel maximum likelihood solution to the PnP problem, that\nincorporates image observation uncertainties and remains real-time capable at\nthe same time. Further, the presented method is general, as is works with 3D\ndirection vectors instead of 2D image points and is thus able to cope with\narbitrary central camera models. This is achieved by projecting (and thus\nreducing) the covariance matrices of the observations to the corresponding\nvector tangent space.","url_abs":"http://arxiv.org/abs/1607.08112v1","url_pdf":"http://arxiv.org/pdf/1607.08112v1.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":"mlpnp-a-real-time-maximum-likelihood-solution","repo_url":"https://github.com/urbste/MLPnP_matlab","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"mlpnp-a-real-time-maximum-likelihood-solution","repo_url":"https://github.com/urbste/MLPnP_matlab_toolbox","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"mlpnp-a-real-time-maximum-likelihood-solution","repo_url":"https://github.com/derleeG/EAPPnP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"mlpnp-a-real-time-maximum-likelihood-solution","repo_url":"https://github.com/MindSpore-scientific/code-14/tree/main/sa-mlp-distilling-graph","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"translation","task_name":"Translation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1607.08112","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}