// Bad Behavior Start $txt['permissionname_badbehavior_goodgroup'] = 'Bad Behavior Whitelist Group'; $txt['permissionhelp_badbehavior_goodgroup'] = 'This option will make a member group exempt from all Bad Behavior tests.'; // Bad Behavior End // Begin Auto Embed Media Pro Text Strings $txt['mediapro_admin'] = 'Simple Audio Video Embedder'; $txt['mediapro_settings'] = 'Settings'; $txt['mediapro_save_settings'] = 'Save Settings'; $txt['mediapro_err_cache'] = 'Cache folder not writable must fix for performance!'; // END Auto Embed Media Pro Text Strings $txt['botscout_mail_subject'] = 'Bot Attempt Stopped'; $txt['botscout_mail_body'] = 'A bot tried to register, but was stopped from doing so.' . "\n\n" . 'Bot Name: %s' . "\n" . 'Bot Email: %s' . "\n" . 'IP Address: %s'; Multi-View Stereo for Community Photo Collections

Author Topic: Multi-View Stereo for Community Photo Collections  (Read 1036 times)

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Multi-View Stereo for Community Photo Collections
« on: April 05, 2011, 04:25:32 PM »
http://grail.cs.washington.edu/projects/mvscpc/

Quote
Abstract
We present a multi-view stereo algorithm that addresses the extreme changes in lighting, scale, clutter, and other effects in large online community photo collections. Our idea is to intelligently choose images to match, both at a per-view and per-pixel level. We show that such adaptive view selection enables robust performance even with dramatic appearance variability. The stereo matching technique takes as input sparse 3D points reconstructed from structure-from-motion methods and iteratively grows surfaces from these points. Optimizing for surface normals within a photoconsistency measure significantly improves the matching results. While the focus of our approach is to estimate high-quality depth maps, we also show examples of merging the resulting depth maps into compelling scene reconstructions. We demonstrate our algorithm on standard multi-view stereo datasets and on casually acquired photo collections of famous scenes gathered from the Internet.
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