The DOI matches its Crossref record.
View interpolation for image synthesis
Open accessAbstract
Image-space simplifications have been used to accelerate the calculation of computer graphic images since the dawn of visual simulation.Texture mapping has been used to provide a means by which images may themselves be used as display primitives.The work reported by this paper endeavors to carry this concept to its logical extreme by using interpolated images to portray three-dimensional scenes.The special-effects technique of morphing, which combines interpolation of texture maps and their shape, is applied to computing arbitrary intermediate frames from an array of prestored images.If the images are a structured set of views of a 3D object or scene, intermediate frames derived by morphing can be used to approximate intermediate 3D transformations of the object or scene.Using the view interpolation approach to synthesize 3D scenes has two main advantages.First, the 3D representation of the scene may be replaced with images.Second, the image synthesis time is independent of the scene complexity.The correspondence between images, required for the morphing method, can be predetermined automatically using the range data associated with the images.The method is further accelerated by a quadtree decomposition and a view-independent visible priority.Our experiments have shown that the morphing can be performed at interactive rates on today's high-end personal computers.Potential applications of the method include virtual holograms, a walkthrough in a virtual environment, image-based primitives and incremental rendering.The method also can be used to greatly accelerate the computation of motion blur and soft shadows cast by area light sources.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Azuma, R. T. (1997) · Presence: Teleoperators and Virtual Environments · doi:10.1162/pres.1997.6.4.355 · Cited by 10,121
Unsupervised Learning of Depth and Ego-Motion from Video
Zhou, T., Brown, M., Snavely, N., & Lowe, D. G. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.700 · Cited by 2,910
Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
Debevec, P. E., Taylor, C. J., & Malik, J. (1996) · Proceedings of the 23rd annual conference on Computer graphics and interactive techniques · doi:10.1145/237170.237191 · Cited by 1,905
QuickTime VR: an image-based approach to virtual environment navigation
Chen, S. E. (1995) · Proceedings of the 22nd annual conference on Computer graphics and interactive techniques - SIGGRAPH '95 · doi:10.1145/218380.218395 · Cited by 1,160
Self-citationShade, J., Gortler, S., He, L.-W., & Szeliski, R. (1998) · Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98 · doi:10.1145/280814.280882 · Cited by 1,115
Metadata
- Authors
- Chen, S. E., & Williams, L.
- Venue
- Proceedings of the 20th annual conference on Computer graphics and interactive techniques
- Publisher
- ACM
- Published
- 1993-09
- Pages
- 279-288
- OpenAlex
- W2098362450
- Cited by
- 1,097
- References
- 0
- FWCI
- 11.57
- Type
- conference paper
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: View interpolation for image synthesis. https://app.cochat.ai/papers/10.1145/166117.166153
- The paper
- Chen, S. E., & Williams, L. (1993). View interpolation for image synthesis. Proceedings of the 20th annual conference on Computer graphics and interactive techniques. https://doi.org/10.1145/166117.166153
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.