The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
A benchmark for 3D mesh segmentation
Abstract
This paper describes a benchmark for evaluation of 3D mesh segmentation salgorithms. The benchmark comprises a data set with 4,300 manually generated segmentations for 380 surface meshes of 19 different object categories, and it includes software for analyzing 11 geometric properties of segmentations and producing 4 quantitative metrics for comparison of segmentations. The paper investigates the design decisions made in building the benchmark, analyzes properties of human-generated and computer-generated segmentations, and provides quantitative comparisons of 7 recently published mesh segmentation algorithms. Our results suggest that people are remarkably consistent in the way that they segment most 3D surface meshes, that no one automatic segmentation algorithm is better than the others for all types of objects, and that algorithms based on non-local shape features seem to produce segmentations that most closely resemble ones made by humans.
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Objective Criteria for the Evaluation of Clustering Methods
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LabelMe: A Database and Web-Based Tool for Image Annotation
Russell, B. C., Torralba, A., Murphy, K. P., & Freeman, W. T. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-007-0090-8 · Cited by 4,210
Shilane, P., Min, P., Kazhdan, M., & Funkhouser, T. (2004) · Proceedings Shape Modeling Applications, 2004. · doi:10.1109/smi.2004.1314504 · Cited by 1,419
Self-citationHoffman, D. D., & Richards, W. A. (1984) · Cognition · doi:10.1016/0010-0277(84)90022-2 · Cited by 1,342
A survey on evaluation methods for image segmentation
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Image segmentation evaluation: A survey of unsupervised methods
Zhang, H., Fritts, J. E., & Goldman, S. A. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.08.003 · Cited by 963
Least squares conformal maps for automatic texture atlas generation
Lévy, B., Petitjean, S., Ray, N., & Maillot, J. (2002) · Proceedings of the 29th annual conference on Computer graphics and interactive techniques · doi:10.1145/566570.566590 · Cited by 943
Least squares conformal maps for automatic texture atlas generation
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Cited by
ShapeNet: An Information-Rich 3D Model Repository
Chang, A. X., Funkhouser, T. A., Guibas, L. J., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., et al. (2023) · doi:10.5281/zenodo.10089705 · Cited by 1,623
Self-citationA scalable active framework for region annotation in 3D shape collections
Yi, L., Kim, V. G., Ceylan, D., Shen, I.-C., Yan, M., Su, H., Lu, C., Huang, Q., Sheffer, A., & Guibas, L. (2016) · ACM Transactions on Graphics · doi:10.1145/2980179.2980238 · Cited by 1,231
A Review on Deep Learning Techniques Applied to Semantic Segmentation
García-García, A., Orts‐Escolano, S., Oprea, S., Villena-Martínez, V., & García‐Rodríguez, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1704.06857 · Cited by 991
Registration of 3D Point Clouds and Meshes: A Survey from Rigid to Nonrigid
Tam, G. K. L., Cheng, Z.-Q., Lai, Y.-K., Langbein, F. C., Liu, Y., Marshall, D., Martin, R. R., Sun, X.-F., & Rosin, P. L. (2013) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2012.310 · Cited by 679
A Survey on Shape Correspondence
van Kaick, O., Zhang, H., Hamarneh, G., & Cohen‐Or, D. (2011) · Computer Graphics Forum · doi:10.1111/j.1467-8659.2011.01884.x · Cited by 606
Metadata
- Authors
- Chen, X., Golovinskiy, A., & Funkhouser, T.
- Venue
- ACM Transactions on Graphics
- Published
- 2009-07-27
- Volume
- 28
- Issue
- 3
- Pages
- 1-12
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2050204708
- Cited by
- 654
- References
- 32
- FWCI
- 43.85
- Type
- journal article
- Language
- en
- Open access
- closed
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