Implicit Active Contours Driven by Local Binary Fitting Energy

By Chunming Li, Chiu Yen Kao, John C. Gore, Zhaohua Ding. 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007

993 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/686bac23cd3879c37e73eafeffb67f138de6c83b

How researchers see this paper

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In Computer Vision and Pattern Recognition

1. Lei Zhang
2. Wen-gang Zhou
3. Ming Liu
4. Kaihua Zhang
5. Ming-Hsuan Yang
6. Haijun Wang
7. Luc Van Gool
8. Huihui Song

Citations in the corpus

• An efficient local Chan-Vese model for image segmentation (2010, methodology): “Here, we also used the recent popular local binary fitting (LBF) model [27] to segment the images in Fig.”
• Active contours driven by local image fitting energy (2010, methodology): “More discussions above the properties of PC model and PS model can be found in [10,11].”
• Localizing Region-Based Active Contours (2008, background): “However, there is no explicit analysis of the appropriate scale on which to localize [ 27 ].”
• A Level Set Approach to Image Segmentation With Intensity Inhomogeneity (2016, neutral): “In this section, we compare our method with the CV model [1], the GCV model [21],1 the LRB model [9],2 the LIC model [11], and the LBF model [10],3 which”
• Minimization of Region-Scalable Fitting Energy for Image Segmentation (2008, result): “Note that our model, originally termed as local binary fitting model, was first presented in [15], and published later in [ 16 ] as a full conference paper.”
• Active contours driven by local Gaussian distribution fitting energy (2009, methodology): “Those procedures make the PS model computationally expensive [16,23].”
• A visual analytics approach to understanding cycling behaviour (2012, neutral): “Arcoumanis et al. [3], were one of the first who studied experimentally the breakup of Diesel droplets using the continuous air jet arrangement.”
• Active contours with selective local or global segmentation: A new formulation and level set method (2010, methodology): “Our proposed SBGFRLS method is general and robust which can be applied to implementing the algorithms of some classical ACMs, such as GAC model [3,4], C–V model [5], PS model [14,15], LBF model [11,24], and so on.”