Global ETD Search

1	Master Texture Space: An Efficient Encoding for Projectively Mapped Objects Guinnip, David 01 January 2005 (has links) Projectively textured models are used in an increasingly large number of applicationsthat dynamically combine images with a simple geometric surface in a viewpoint dependentway. These models can provide visual fidelity while retaining the effects affordedby geometric approximation such as shadow casting and accurate perspective distortion.However, the number of stored views can be quite large and novel views must be synthesizedduring the rendering process because no single view may correctly texture the entireobject surface. This work introduces the Master Texture encoding and demonstrates thatthe encoding increases the utility of projectively textured objects by reducing render-timeoperations. Encoding involves three steps; 1) all image regions that correspond to the samegeometric mesh element are extracted and warped to a facet of uniform size and shape,2) an efficient packing of these facets into a new Master Texture image is computed, and3) the visibility of each pixel in the new Master Texture data is guaranteed using a simplealgorithm to discard occluded pixels in each view. Because the encoding implicitly representsthe multi-view geometry of the multiple images, a single texture mesh is sufficientto render the view-dependent model. More importantly, every Master Texture image cancorrectly texture the entire surface of the object, removing expensive computations suchas visibility analysis from the rendering algorithm. A benefit of this encoding is the supportfor pixel-wise view synthesis. The utility of pixel-wise view synthesis is demonstratedwith a real-time Master Texture encoded VDTM application. Pixel-wise synthesis is alsodemonstrated with an algorithm that distills a set of Master Texture images to a singleview-independent Master Texture image.
2	A See-ability Metric to Improve Mini Unmanned Aerial Vehicle Operator Awareness Using Video Georegistered to Terrain Models Engh, Cameron Howard 20 November 2008 (has links) (PDF) Search and rescue operations conducted in wilderness environments can be greatly aided by the use of video filmed from mini-UAVs. While lightweight, inexpensive and easily transportable, these small aircraft suffer from wind buffeting and may produce video that is difficult to search. To aid in the video search process, we have created a system to project video frames into a 3D representation of the search region. This projection allows us to tie each frame of video to a real-world location, enabling a myriad of novel views, mosaics and metrics that can be used to guide the search including a new metric dubbed “see-ability.” The “see-ability” metric is the primary contribution of this research as it indicates what portion of the search area has been viewed and provides an estimate of the quality of that viewing. The research includes a validation of the “see-ability” metric as it correlates to objective performance in the search task by real people. BYU Brigham Young University computer vision seeability see-ability MiniUAV MUAV georegister georegistration terrain unmanned air vehicle aerial terrain model SAR search rescue search and rescue projective texture video telemetry video indexing visibility Computer Sciences

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Master Texture Space: An Efficient Encoding for Projectively Mapped Objects

A See-ability Metric to Improve Mini Unmanned Aerial Vehicle Operator Awareness Using Video Georegistered to Terrain Models