Computer Graphics and Visualization Lab
Department of Computer Science at Purdue University

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projects 2011/10/17 18:59 projects 2011/10/18 16:04 current
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^ **Acquisition and Modeling**  ^^ ^ **Acquisition and Modeling**  ^^
^ {{:wiki:projects:virtual_restoration:restore.jpg?160|}} ^ **[[projects:appearance_editing|Appearance Editing: Modifying the Appearance of Real-World Objects]]** \\ \\ Appearance editing offers a unique way to view visually altered objects with various appearances or visualizations. By carefully controlling how an object is illuminated using digital projectors, we obtain stereoscopic imagery for any number of observers with everything visible to the naked eye (i.e., no need for head-mounts or goggles). Such an ability is useful for various applications, including scientific visualization, virtual restoration of cultural heritage, and display systems.  ^ ^ {{:wiki:projects:virtual_restoration:restore.jpg?160|}} ^ **[[projects:appearance_editing|Appearance Editing: Modifying the Appearance of Real-World Objects]]** \\ \\ Appearance editing offers a unique way to view visually altered objects with various appearances or visualizations. By carefully controlling how an object is illuminated using digital projectors, we obtain stereoscopic imagery for any number of observers with everything visible to the naked eye (i.e., no need for head-mounts or goggles). Such an ability is useful for various applications, including scientific visualization, virtual restoration of cultural heritage, and display systems.  ^
-^ {{:wiki:projects:urban.jpg?160|}} ^ **[[projects:urban|Urban Modeling and Visualization]]** \\ \\ Our project efforts have focused on obtaining digital models of large-scale urban structures in order to enable simulating physical phenomena and human activities in city-size environments. To date, we have developed several algorithms and large-scale software systems using ground-level imagery, aerial imagery, GIS data, and forward and inverse procedural modeling to create/modify 3D and 2D urban models.  ^+^ {{:wiki:projects:urban.jpg?160|}} ^ **[[http://www.cs.purdue.edu/cgvlab/urban/|Urban Modeling and Visualization]]** \\ \\ Our project efforts have focused on obtaining digital models of large-scale urban structures in order to enable simulating physical phenomena and human activities in city-size environments. To date, we have developed several algorithms and large-scale software systems using ground-level imagery, aerial imagery, GIS data, and forward and inverse procedural modeling to create/modify 3D and 2D urban models.  ^
^ {{:wiki:projects:gensig:gensig.jpg?160|}} ^ **[[projects:genuinity |Embedding Information into Physical Objects]]** \\ \\ Our work provides methods to embed into a physical object information for a variety of purposes, including genuinity detection, tamper detection, and multiple appearance generation. Genuinity detection refers to encoding fragile or robust signatures so that a copy, or tampered, version can be differentiated from the original object. Multiple appearance generation refers to generalizing the encoded information from a signature to a different appearance of the same physical object.  ^ ^ {{:wiki:projects:gensig:gensig.jpg?160|}} ^ **[[projects:genuinity |Embedding Information into Physical Objects]]** \\ \\ Our work provides methods to embed into a physical object information for a variety of purposes, including genuinity detection, tamper detection, and multiple appearance generation. Genuinity detection refers to encoding fragile or robust signatures so that a copy, or tampered, version can be differentiated from the original object. Multiple appearance generation refers to generalizing the encoded information from a signature to a different appearance of the same physical object.  ^
^ {{:wiki:projects:pgm.png?160|}} ^ **[[projects:photogeometric|A Photogeometric Framework for Capturing 3D Objects]]** \\ \\ We introduce a photogeometric framework for acquiring 3D objects with sub-millimeter accuracy. The defining characteristic of our framework is leveraging the complementary advantages of photometric and geometric acquisition. The two approaches are tightly integrated in an iterative acquisition process that achieves self-calibration, multi-viewpoint sampling, and high level of detail.  ^ ^ {{:wiki:projects:pgm.png?160|}} ^ **[[projects:photogeometric|A Photogeometric Framework for Capturing 3D Objects]]** \\ \\ We introduce a photogeometric framework for acquiring 3D objects with sub-millimeter accuracy. The defining characteristic of our framework is leveraging the complementary advantages of photometric and geometric acquisition. The two approaches are tightly integrated in an iterative acquisition process that achieves self-calibration, multi-viewpoint sampling, and high level of detail.  ^
 

projects.txt · Last modified: 2011/10/18 16:04 by cvanegas
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