The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Active appearance models
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Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Efficient region tracking with parametric models of geometry and illumination
Hager, G. D., & Belhumeur, P. N. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.722606 · Cited by 1,066
Cited by
Yushkevich, P. A., Piven, J., Hazlett, H. C., Smith, R. G., Ho, S., Gee, J. C., & Gerig, G. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.015 · Cited by 8,868
Cootes, T. F., Edwards, G. J., & Taylor, C. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927467 · Cited by 5,409
Self-citationFrom few to many: illumination cone models for face recognition under variable lighting and pose
Georghiades, A. S., Belhumeur, P. N., & Kriegman, D. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927464 · Cited by 4,912
A Bayesian model of shape and appearance for subcortical brain segmentation
Patenaude, B., Smith, S. M., Kennedy, D. N., & Jenkinson, M. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.046 · Cited by 2,287
Automatic analysis of facial expressions: the state of the art
Pantie, M., & Rothkrantz, L. J. M. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.895976 · Cited by 1,778
Deep Convolutional Network Cascade for Facial Point Detection
Sun, Y., Wang, X., & Tang, X. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.446 · Cited by 1,382
Ultrasound image segmentation: a survey
Noble, J. A., & Boukerroui, D. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.877092 · Cited by 1,157
Age Synthesis and Estimation via Faces: A Survey
Fu, Y., Guo, G., & Huang, T. S. (2010) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.36 · Cited by 569
Statistical models of appearance for medical image analysis and computer vision:
Cootes, T. F., & Taylor, C. J. (2001) · SPIE Proceedings · doi:10.1117/12.431093 · Cited by 429
Self-citationFast and sequence-adaptive whole-brain segmentation using parametric Bayesian modeling
Puonti, O., Iglesias, J. E., & Van Leemput, K. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.011 · Cited by 258
Estimating average growth trajectories in shape-space using kernel smoothing
Hutton, T. J., Buxton, B. F., Hammond, P., & Potts, H. W. W. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.814784 · Cited by 117
Training cnns for image registration from few samples with model-based data augmentation
Uzunova, H., Wilms, M., Handels, H., & Ehrhardt, J. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-66182-7_26 · Cited by 110
Relative pose estimation for cylinder-shaped spacecrafts using single image
Liu, C., & Hu, W. (2014) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2014.120757 · Cited by 101
Total Moving Face Reconstruction
Suwajanakorn, S., Kemelmacher-Shlizerman, I., & Seitz, S. M. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10593-2_52 · Cited by 93
Deep Differentiable Random Forests for Age Estimation
Shen, W., Guo, Y., Wang, Y., Zhao, K., Wang, B., & Yuille, A. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2937294 · Cited by 91
Zhao, X., Huang, D., Dellandrea, E., & Chen, L. (2010) · 2010 20th International Conference on Pattern Recognition · doi:10.1109/icpr.2010.907 · Cited by 66
3D Assisted Face Recognition: A Survey of 3D Imaging, Modelling and Recognition Approachest
Kittler, J., Hilton, A., Hamouz, M., & Illingworth, J. (2006) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops · doi:10.1109/cvpr.2005.377 · Cited by 45
Automated analysis of craniofacial morphology using magnetic resonance images
Chakravarty, M. M., Aleong, R., Leonard, G., Perron, M., Pike, G. B., Richer, L., Veillette, S., Pausova, Z., & Paus, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020241 · Cited by 22
Sharifnejad, M., Shahbahrami, A., Akoushideh, A., & Hassanpour, R. Z. (2021) · IET Image Processing · doi:10.1049/ipr2.12037 · Cited by 19
“Two efficient methods for geometrical feature extraction are active appearance model (AAM) [13] and active shape model (ASM) [14].”
MethodInfluential
Metadata
- Authors
- Cootes, T. F., Edwards, G. J., & Taylor, C. J.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 1998
- Pages
- 484-498
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2172803778
- Cited by
- 2,195
- References
- 2
- FWCI
- 42.90
- Type
- conference paper
- Language
- en
- Open access
- closed
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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.
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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.
