The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Real-time 3D model acquisition
Abstract
The digitization of the 3D shape of real objects is a rapidly expanding field, with applications in entertainment, design, and archaeology. We propose a new 3D model acquisition system that permits the user to rotate an object by hand and see a continuously-updated model as the object is scanned. This tight feedback loop allows the user to find and fill holes in the model in real time, and determine when the object has been completely covered. Our system is based on a 60 Hz. structured-light rangefinder, a real-time variant of ICP (iterative closest points) for alignment, and point-based merging and rendering algorithms. We demonstrate the ability of our prototype to scan objects faster and with greater ease than conventional model acquisition pipelines.
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
Cites
Object modeling by registration of multiple range images
Chen, Y., & Medioni, G. (2002) · Proceedings. 1991 IEEE International Conference on Robotics and Automation · doi:10.1109/robot.1991.132043 · Cited by 1,409
Cited by
KinectFusion: Real-time dense surface mapping and tracking
Newcombe, R. A., Fitzgibbon, A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A. J., Kohi, P., Shotton, J., & Hodges, S. (2011) · 2011 10th IEEE International Symposium on Mixed and Augmented Reality · doi:10.1109/ismar.2011.6092378 · Cited by 4,008
KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera
Izadi, S., Kim, D., Hilliges, O., Molyneaux, D., Newcombe, R., Kohli, P., Shotton, J., Hodges, S., Freeman, D., Davison, A., et al. (2011) · Proceedings of the 24th annual ACM symposium on User interface software and technology · doi:10.1145/2047196.2047270 · Cited by 2,110
Learning Joint Reconstruction of Hands and Manipulated Objects
Hasson, Y., Varol, G., Tzionas, D., Kalevatykh, I., Black, M. J., Laptev, I., & Schmid, C. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.01208 · Cited by 513
Intel(R) RealSense(TM) Stereoscopic Depth Cameras
Keselman, L., Woodfill, J. I., Grunnet-Jepsen, A., & Bhowmik, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.167 · Cited by 448
Real-Time 3D Reconstruction in Dynamic Scenes Using Point-Based Fusion
Keller, M., Lefloch, D., Lambers, M., Izadi, S., Weyrich, T., & Kolb, A. (2013) · 2013 International Conference on 3D Vision · doi:10.1109/3dv.2013.9 · Cited by 384
Metadata
- Authors
- Rusinkiewicz, S., Hall-Holt, O., & Levoy, M.
- Venue
- Proceedings of the 29th annual conference on Computer graphics and interactive techniques
- Publisher
- ACM
- Published
- 2002-07
- Pages
- 438-446
- OpenAlex
- W2247810280
- Cited by
- 576
- References
- 1
- FWCI
- 65.92
- Type
- conference paper
- Language
- en
- Open access
- closed
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: Real-time 3D model acquisition. https://app.cochat.ai/papers/10.1145/566570.566600
- The paper
- Rusinkiewicz, S., Hall-Holt, O., & Levoy, M. (2002). Real-time 3D model acquisition. Proceedings of the 29th annual conference on Computer graphics and interactive techniques. https://doi.org/10.1145/566570.566600
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.
