{"id":76000,"date":"2025-02-08T15:05:32","date_gmt":"2025-02-08T15:05:32","guid":{"rendered":"https:\/\/peraltafinancing.com\/animation\/trust-region-eigenvalue-filtering-for-projected-newton-physics-based-animation\/"},"modified":"2025-02-08T15:05:32","modified_gmt":"2025-02-08T15:05:32","slug":"trust-region-eigenvalue-filtering-for-projected-newton-physics-based-animation","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=76000","title":{"rendered":"Trust-Region Eigenvalue Filtering for Projected Newton \u00bb Physics-Based Animation"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div id=\"post-4095\">\n<div class=\"itemtext\">\n<p>Honglin Chen, Hseuh-Ti Derek Liu, Alec Jacobson, David I. W. Levin, Changxi Zheng<\/p>\n<p>We introduce a novel adaptive eigenvalue filtering strategy to stabilize and accelerate the optimization of Neo-Hookean energy and its variants under the Projected Newton framework. For the first time, we show that Newton\u2019s method, Projected Newton with eigenvalue clamping and Projected Newton with absolute eigenvalue filtering can be unified using ideas from the generalized trust region method. Based on the trust-region fit, our model adaptively chooses the correct eigenvalue filtering strategy to apply during the optimization. Our method is simple but effective, requiring only two lines of code change in the existing Projected Newton framework. We validate our model outperforms stand-alone variants across a number of experiments on quasistatic simulation of deformable solids over a large dataset.<\/p>\n<p><a href=\"https:\/\/www.cs.columbia.edu\/cg\/trust-region\/\">Trust-Region Eigenvalue Filtering for Projected Newton<\/a><\/p>\n<\/p><\/div>\n<div class=\"postinfo\">\n\t\t\t<span class=\"postmeta\">Posted by christopherbatty on <a href=\"https:\/\/www.physicsbasedanimation.com\/2024\/11\/23\/trust-region-eigenvalue-filtering-for-projected-newton\/\">November 23rd, 2024<\/a> <\/span><br \/>\n\t\t\t\t\t\t<span class=\"postcats\">Posted in <a href=\"https:\/\/www.physicsbasedanimation.com\/category\/uncategorized\/\" rel=\"category tag\">Uncategorized<\/a><\/span><br \/>\n\t\t\t\t\t\t\t\t\t<span class=\"posttags\"\/>\n\t\t\t\t<\/div>\n<p>\t\t\t\t\t<!--\n\t\t\t\t<rdf:RDF xmlns:rdf=\"http:\/\/www.w3.org\/1999\/02\/22-rdf-syntax-ns#\"\n\t\t\txmlns:dc=\"http:\/\/purl.org\/dc\/elements\/1.1\/\"\n\t\t\txmlns:trackback=\"http:\/\/madskills.com\/public\/xml\/rss\/module\/trackback\/\">\n\t\t<rdf:Description rdf:about=\"https:\/\/www.physicsbasedanimation.com\/2024\/11\/23\/trust-region-eigenvalue-filtering-for-projected-newton\/\"\n    dc:identifier=\"https:\/\/www.physicsbasedanimation.com\/2024\/11\/23\/trust-region-eigenvalue-filtering-for-projected-newton\/\"\n    dc:title=\"Trust-Region Eigenvalue Filtering for Projected Newton\"\n    trackback:ping=\"https:\/\/www.physicsbasedanimation.com\/2024\/11\/23\/trust-region-eigenvalue-filtering-for-projected-newton\/trackback\/\" \/>\n<\/rdf:RDF>\t\t\t-->\n\t\t<\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>Honglin Chen, Hseuh-Ti Derek Liu, Alec Jacobson, David I. W. Levin, Changxi Zheng We introduce a novel adaptive eigenvalue filtering strategy to stabilize and accelerate the optimization of Neo-Hookean energy and its variants under the Projected Newton framework. For the first time, we show that Newton\u2019s method, Projected Newton with eigenvalue clamping and Projected Newton [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":4302,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[12035],"tags":[6119,38925,38926,38203,18075,38927,38924],"dealstore":[],"offerexpiration":[],"class_list":["post-76000","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-animation","tag-animation","tag-eigenvalue","tag-filtering","tag-newton","tag-physicsbased","tag-projected","tag-trustregion"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Trust-Region Eigenvalue Filtering for Projected Newton \u00bb Physics-Based Animation - Som2ny Network<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fivemor.com\/?p=76000\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Trust-Region Eigenvalue Filtering for Projected Newton \u00bb Physics-Based Animation - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"Honglin Chen, Hseuh-Ti Derek Liu, Alec Jacobson, David I. W. Levin, Changxi Zheng We introduce a novel adaptive eigenvalue filtering strategy to stabilize and accelerate the optimization of Neo-Hookean energy and its variants under the Projected Newton framework. For the first time, we show that Newton\u2019s method, Projected Newton with eigenvalue clamping and Projected Newton [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fivemor.com\/?p=76000\" \/>\n<meta property=\"og:site_name\" content=\"Som2ny Network\" \/>\n<meta property=\"article:published_time\" content=\"2025-02-08T15:05:32+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/fivemor.com\/wp-content\/uploads\/2025\/01\/blank.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"200\" \/>\n\t<meta property=\"og:image:height\" content=\"200\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fivemor.com\/?p=76000#article\",\"isPartOf\":{\"@id\":\"https:\/\/fivemor.com\/?p=76000\"},\"author\":{\"name\":\"admin\",\"@id\":\"https:\/\/fivemor.com\/#\/schema\/person\/b85e3c3dc0e1daea076524dc8810c371\"},\"headline\":\"Trust-Region Eigenvalue Filtering for Projected Newton \u00bb Physics-Based Animation\",\"datePublished\":\"2025-02-08T15:05:32+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fivemor.com\/?p=76000\"},\"wordCount\":156,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fivemor.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/fivemor.com\/?p=76000#primaryimage\"},\"thumbnailUrl\":\"https:\/\/fivemor.com\/wp-content\/uploads\/2025\/01\/blank.jpg\",\"keywords\":[\"Animation\",\"Eigenvalue\",\"Filtering\",\"Newton\",\"PhysicsBased\",\"Projected\",\"TrustRegion\"],\"articleSection\":[\"Animation\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fivemor.com\/?p=76000#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fivemor.com\/?p=76000\",\"url\":\"https:\/\/fivemor.com\/?p=76000\",\"name\":\"Trust-Region Eigenvalue Filtering for Projected Newton \u00bb Physics-Based Animation - 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