My second major innovation is a series of methods that enable foreground removal from single images of buildings or brick walls without any motion information. The key insight is to use a priori knowledge about grid patterns on building facades that can be modeled as Near Regular Textures (NRT). I describe a Markov Random Field (MRF) model for such textures and introduce a Markov Chain Monte Carlo (MCMC) optimization procedure for discovering grid structures on building images. Results are shown on both synthetic NRT as well as building images. This simple spatial rule is then used as a starting point for inference of missing windows, facade segmentation, grammar-based image parsing, outlier identification, and foreground removal.... architects used materials like plastic, foam, wood or paper to create models from elaborate manual measurements. ... The success of recent products like Google Earth, SketchUp, and Microsoft Virtual Earth has enabled urban modeling toanbsp;...
|Title||:||Robust Spatiotemporal Analysis of Architectural Imagery|
|Publisher||:||ProQuest - 2007|