The DOI matches its Crossref record.
The lumigraph
Open accessAbstract
This paper discusses a new method for capturing the complete appearance of bothsynthetic and real world objects and scenes,representing this information, and then using this representation to render images of the object from new camera positions.Unlike the shape capture process traditionally used in computer vision and the rendering process traditionally used in computer graphics, our approach does not rely on geometric representations.Instead we sample and reconstruct a 4D function.which we call a Lumigraph.The Lumigraph is a subset o f the complete plenoptic fu nction that describes the flow of light at all positions in all directions.With the Lumigraph.new images of the object can be generated very quick]y,independentof the geometric or illumination complexity of the scene or object.The paper discusses a complete working system including the capture of sainples.the construction of the Lumigraph, and thesubsequent rendering of images from this new representation.even i f given accurate geometric models.Quicktime V R [6] was one ofthe first systems to suggest that the traditional modeling/rendering process can beskipped.Instead.
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
3D Gaussian Splatting for Real-Time Radiance Field Rendering
Kerbl, B., Kopanas, G., Leimkuehler, T., & Drettakis, G. (2023) · ACM Transactions on Graphics · doi:10.1145/3592433 · Cited by 6,025
“The first novel-view synthesis approaches were based on light fields, first densely sampled [Gortler et al. 1996; Levoy and Hanrahan 1996] then allowing unstructured capture [Buehler et al. 2001].”
MethodNeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
Mildenhall, B., Srinivasan, P. P., Tancik, M., Barron, J. T., Ramamoorthi, R., & Ng, R. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58452-8_24 · Cited by 5,351
Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields
Barron, J. T., Mildenhall, B., Tancik, M., Hedman, P., Martin-Brualla, R., & Srinivasan, P. P. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv48922.2021.00580 · Cited by 1,921
Shade, 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
Self-citationDirect Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction
Sun, C., Sun, M., & Chen, H.-T. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.00538 · Cited by 939
Metadata
- Authors
- Gortler, S. J., Grzeszczuk, R., Szeliski, R., & Cohen, M. F.
- Venue
- Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
- Publisher
- ACM
- Published
- 1996-08
- Pages
- 43-54
- OpenAlex
- W2294985758
- Cited by
- 2,458
- References
- 0
- FWCI
- 36.71
- 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: The lumigraph. https://app.cochat.ai/papers/10.1145/237170.237200
- The paper
- Gortler, S. J., Grzeszczuk, R., Szeliski, R., & Cohen, M. F. (1996). The lumigraph. Proceedings of the 23rd annual conference on Computer graphics and interactive techniques. https://doi.org/10.1145/237170.237200
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.
