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Demetri Terzopoulos
Researcher at University of California, Los Angeles
Publications - 339
Citations - 50795
Demetri Terzopoulos is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Animation & Image segmentation. The author has an hindex of 77, co-authored 331 publications receiving 47881 citations. Previous affiliations of Demetri Terzopoulos include University of California, Berkeley & Seikei University.
Papers
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Journal ArticleDOI
Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Journal ArticleDOI
Deformable models in medical image analysis: a survey
TL;DR: The rapidly expanding body of work on the development and application of deformable models to problems of fundamental importance in medical image analysis, including segmentation, shape representation, matching and motion tracking is reviewed.
Proceedings ArticleDOI
Elastically deformable models
TL;DR: The description of shape and the description of motion are unified and differential equations that model the behavior of non-rigid curves, surfaces, and solids as a function of time are constructed.
Book ChapterDOI
Multilinear Analysis of Image Ensembles: TensorFaces
TL;DR: This work considers the multilinear analysis of ensembles of facial images that combine several modes, including different facial geometries (people), expressions, head poses, and lighting conditions, and concludes that the resulting "TensorFaces" representation has several advantages over conventional eigenfaces.
Posted Content
Image Segmentation Using Deep Learning: A Survey
Shervin Minaee,Yuri Boykov,Fatih Porikli,Antonio Plaza,Nasser Kehtarnavaz,Demetri Terzopoulos +5 more
TL;DR: A comprehensive review of recent pioneering efforts in semantic and instance segmentation, including convolutional pixel-labeling networks, encoder-decoder architectures, multiscale and pyramid-based approaches, recurrent networks, visual attention models, and generative models in adversarial settings are provided.