Dynamical statistical shape priors for level set-based tracking

By Daniel Cremers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006

319 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/e815dc457e71cdbd93f6176768da6b03ee667316

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Citations in the corpus

A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape (2007, background): “From left to right, the shape priors are static (a single shape), uniformly distributed in the PCA subspace, automatically selected from multiple shape instances [24] and dynamical [18].”
TouchCut: Fast image and video segmentation using single-touch interaction (2014, methodology): “Finally, our proposed model also utilizes the geometric cue implied in single-touch input, that users typically touch image in close vicinity to the geometric center of the desired object.”
Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation (2006, background): “More recently, level set formulations were proposed which allow to impose dynamical shape priors ( Cremers, 2006 ) and concepts of tracking (Rathi et al., 2005), to apply shape knowledge selectively in certain image regions (Cremers, Sochen and Schn¨ orr, 2003; Chan and Zhu, 2003), or to impose mult”
A survey of graph theoretical approaches to image segmentation (2013, background): “[21,78] to specify the template as a distance function whose zero level set corresponds to the template.”
Hough-based tracking of non-rigid objects (2011, background): “, [8]), use only very simple object appearance models (e.”
Video Segmentation by Tracking Many Figure-Ground Segments (2013, background): “Besides the video segmentation work that utilizes segment tracking [29, 34, 6], a great deal of research have been on segment tracking with active contours [13, 28, 5], which require a user-drawn region in the first frame.”
Graph Cuts and Efficient N-D Image Segmentation (2006, background): “The same basic idea is widely used in level-sets, e.g. (Cremers et al., 2006; Cremers, 2006).”