{"id":343,"date":"2016-02-24T19:13:10","date_gmt":"2016-02-24T18:13:10","guid":{"rendered":"http:\/\/babel.isa.uma.es\/kipr\/?p=343"},"modified":"2016-02-24T19:13:10","modified_gmt":"2016-02-24T18:13:10","slug":"using-multiple-ransacs-for-tracking","status":"publish","type":"post","link":"https:\/\/babel.isa.uma.es\/kipr\/?p=343","title":{"rendered":"Using multiple RANSACs for tracking"},"content":{"rendered":"<h4>Peter C. Niedfeldt and Randal W. Beard, <strong>Convergence and Complexity Analysis of Recursive-RANSAC: A New Multiple Target Tracking Algorithm,<\/strong> in IEEE Transactions on Automatic Control , vol.61, no.2, pp.456-461, Feb. 2016, <a href=\"http:\/\/doi.org\/10.1109\/TAC.2015.2437518\" target=\"_blank\">DOI: 10.1109\/TAC.2015.2437518<\/a>.<\/h4>\n<blockquote><p>The random sample consensus (RANSAC) algorithm was developed as a regression algorithm that robustly estimates the parameters of a single signal in clutter by forming many simple hypotheses and computing how many measurements support that hypothesis. In essence, RANSAC estimates the data association problem of a single target in clutter by identifying the hypothesis with the most supporting measurements. The newly developed recursive-RANSAC (R-RANSAC) algorithm extends the traditional RANSAC algorithm to track multiple targets recursively by storing a set of hypotheses between time steps. In this technical note we show that R-RANSAC converges to the minimum mean-squared solution for well-spaced targets. We also show that the worst-case computational complexity of R-RANSAC is quadratic in the number of new measurements and stored models.\n<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Peter C. Niedfeldt and Randal W. Beard, Convergence and Complexity Analysis of Recursive-RANSAC: A New Multiple Target Tracking Algorithm, in <span class=\"ellipsis\">&hellip;<\/span> <span class=\"more-link-wrap\"><a href=\"https:\/\/babel.isa.uma.es\/kipr\/?p=343\" class=\"more-link\"><span>Read More &rarr;<\/span><\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[40],"tags":[163,164],"class_list":["post-343","post","type-post","status-publish","format-standard","hentry","category-mathematics","tag-ransac","tag-tracking"],"_links":{"self":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/343"}],"collection":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=343"}],"version-history":[{"count":1,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/343\/revisions"}],"predecessor-version":[{"id":344,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/343\/revisions\/344"}],"wp:attachment":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=343"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=343"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=343"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}