Image-based modeling and rendering
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In computer graphics and computer vision, image-based modeling and rendering (IBMR) methods rely on a set of two-dimensional images of a scene to generate a three-dimensional model and then render some novel views of this scene.
The traditional approach of computer graphics has been to create a geometric model in 3D and try to reproject it onto a two-dimensional image. Computer vision, conversely, is mostly focused on detecting, grouping, and extracting features (edges, faces, etc.) present a given picture and then trying to interpret them as three-dimensional clues. Image-based modeling and rendering allows the use of multiple two-dimensional images in order to generate directly novel two-dimensional images, skipping the manual modeling stage.
Instead of considering only the physical model of a solid, IBMR methods usually focus more on light modeling. The fundamental concept behind IBMR is the plenoptic illumination function which is a parametrisation of the light field. The plenoptic function describes the light rays contained in a given volume. It can be represented with seven dimensions: a ray is defined by its position (x,y,z), its orientation (θ,φ), its wave length (λ) and its time (t): P(x,y,z,θ,φ,λ,t). IBMR methods try to approximate the plenoptic function to render a novel set of two-dimensional images from another. Given the high dimensionality of this function, practical methods place constraints on the parameters in order to reduce this number (typically to 2 to 4).
[edit] IBMR methods and algorithms
- View morphing generates a transition between images
- Panoramic imaging renders panoramas using image mosaics of individual still images
- Lumigraph relies on a dense sampling of a scene
- Space carving generates a 3D model based on a photo-consistency check
