Image-based modeling and rendering: Difference between revisions

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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 [[3D reconstruction from multiple images|generate a three-dimensional model]] and then [[rendering (computer graphics)|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 wave lengthwavelength <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==

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== 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]

*[http://www.cs.ucl.ac.uk/staff/r.freeman/ Mixed Reality Toolkit (MRT)] - [[University College London]]

* {{cite journal

*[http://insight3d.sourceforge.net/ insight3d ] - open source image-based 3d modeling software

|author1=Ce Zhu |author2=Shuai Li | title=Depth Image Based View Synthesis: New Insights and Perspectives on Hole Generation and Filling

*[http://www.cs.washington.edu/homes/ccwu/vsfm/ VisualSFM] - GUI application of Multicore-accelerated SFM

| 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

}}

{{MixedComputer realitygraphics}}

[[Category:Computer graphics]]

[[Category:Mixed reality]]

[[Category:Applications of computer vision]]

[[Category:Mixed3D realityimaging]]

{{compu-sci-stub}}