In this talk, I will provide a complete framework for using multi-perspective imaging models in computer vision and graphics. Our multi-perspective framework consists of four key components: acquisition, reconstruction, rendering, and display. A multi-perspective camera captures a scene from multiple viewpoints in a single image. From the input image, intelligent software can recover 3D scene geometry using multi-perspective stereo matching algorithms or via shape-from-distortion approaches. Our solutions are particularly useful for reconstructing specular (reflective and refractive) surfaces such as dynamic 3D fluid surfaces which can also be viewed as general multi-perspective cameras. The recovered geometry, along with lighting and surface reflectance, can then be loaded into a new multi-perspective graphics pipeline for real-time rendering. Finally, we can visualize the rendering results on a special multi-perspective display that combines a single consumer projector and specially-shaped mirrors/lenses. Such displays will offer an unprecedented level of flexibility in terms of aspect ratio, size, field of view, etc.
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Spring 2012 GRASP Seminar – Jingyi Yu, University of Delaware, “Beyond Perspective Cameras: Multi-perspective Imaging, Reconstruction, Rendering and Projection”
January 27, 2012 @ 11:00 am - 12:00 pm
Abstract: A perspective image represents the spatial relationships of objects in a scene as they appear from a single viewpoint. In contrast, a multi-perspective image combines what is seen from several viewpoints into a single image. Despite their incongruity of view, effective multi-perspective images are able to preserve spatial coherence and can depict, within a single context, details of a scene that are simultaneously inaccessible from a single view.