| abstract
| - In between computer graphics and computer vision, Image-Based Modeling and Rendering (IBMR) methods rely on a set of images (Image-Based) of a scene to generate a three-dimensional model (Modeling) and/or some novel views (Rendering (computer graphics)) of this scene. 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, at the opposite, is mostly focused on searching features in a pictures and trying to interprete them as three-dimensional clues. Image-Based Modelling and Rendering would allow to use one or several two-dimensional images in order to generate directly novel two-dimensional images, skipping the modelisation stage. Instead of considering only the physical model of a solid, IBMR methods usually focus more on light modelling. Therefore 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 , its orientation , its wave length and its time : . 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, most of the methods put constraints in order to reduce this number (typically to 2 to 4). A couple of well-known IBMR methods and algorithms are the following: View Morphing generates a transition between images, QuickTime VR renders panoramas using image mosaics, Lumigraph relies on a dense sampling of the scene and Space Carving generates a 3D model based on a photo-consistency check.
- 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 in 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.
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