{{Short description|Computer imaging technique}} {{no footnotes|date=April 2019}} 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 used 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.
== Light modeling == 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 <math>(x,y,z)</math>, its orientation <math>(\theta,\phi)</math>, its wavelength <math>(\lambda)</math> and its time <math>(t)</math>: <math>P (x,y,z,\theta,\phi,\lambda,t)</math>. 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).
==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 <!--The above deserve better explanations here-->
== See also == * View synthesis * 3D reconstruction * Structure from motion
== References == {{reflist}}
==External links== * Quan, Long. ''Image-based modeling''. Springer Science & Business Media, 2010. [https://www.springer.com/us/book/9781441966780] * {{cite journal |author1=Ce Zhu |author2=Shuai Li | title=Depth Image Based View Synthesis: New Insights and Perspectives on Hole Generation and Filling | journal=IEEE Transactions on Broadcasting | volume=62 | pages= 82–93 |date=2016 | doi=10.1109/TBC.2015.2475697 | issue=1 |s2cid=19100077 }} * {{cite journal |author1=Mansi Sharma |author2=Santanu Chaudhury |author3=Brejesh Lall |author4=M.S. Venkatesh | title=A flexible architecture for multi-view 3DTV based on uncalibrated cameras | journal=Journal of Visual Communication and Image Representation | volume=25 | pages= 599–621 |date=2014 | doi=10.1016/j.jvcir.2013.07.012 | issue=4 }} * {{cite conference |author1=Mansi Sharma |author2=Santanu Chaudhury |author3=Brejesh Lall | conference=In 22nd International Conference on Pattern Recognition (ICPR), Stockholm, 2014 | title=Kinect-Variety Fusion: A Novel Hybrid Approach for Artifacts-Free 3DTV Content Generation | date=2014 | doi=10.1109/ICPR.2014.395 }} * {{cite conference |author1=Mansi Sharma |author2=Santanu Chaudhury |author3=Brejesh Lall | conference=Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing, ACM New York, NY, USA | title=3DTV view generation with virtual pan/tilt/zoom functionality | date=2012 | doi=10.1145/2425333.2425374 | url=http://dl.acm.org/citation.cfm?id=2425374 | url-access=subscription }}
{{Computer graphics}}
Category:Computer graphics Category:Applications of computer vision Category:3D imaging