Description of Interest Regions with Center-Symmetric Local Binary Patterns
By Marko Heikkilä, Matti Pietikäinen, Cordelia Schmid. Indian Conference on Computer Vision, Graphics & Image Processing, 2006
381 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/aeeb5d9d80acacc2bd2567246d92cb83a7b3734d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Lior Wolf
- Matti Pietikäinen
- Ramachandra Raghavendra
- Christoph Busch
- Tal Hassner
- Lahav Yeffet
- Marko Heikkilä
- Xiaogang Wang
In Computer Vision and Pattern Recognition
- Xiaogang Wang
- Luc Van Gool
- Dacheng Tao
- Lior Wolf
- Andrew Zisserman
- Tal Hassner
- Cordelia Schmid
- Xiaoou Tang
Citations in the corpus
- A Linear Time Histogram Metric for Improved SIFT Matching (2008, background): “Histograms of oriented gradient descriptors [3–6] are ubiquitous tools in numerous computer vision tasks.”
- Face recognition in unconstrained videos with matched background similarity (2011, methodology): “Following a conversion to grayscale, the images are aligned by fixing the coordinates of automatically detected facial feature points [2], and we apply the following descriptors: Local Binary Patterns (LBP) [8], Center- Symmetric LBP (CSLBP) [5] and Four-Patch LBP [21].”
- Local binary features for texture classification: Taxonomy and experimental study (2017, methodology): “Center Symmetric Local Binary Pattern CS-LBP Image Matching 2009 [37,6]”
- SHREC'14 Track: Large Scale Comprehensive 3D Shape Retrieval (2014, methodology): “For the first three runs, we applied CSLBP*, a hybrid shape descriptor, composed of C enter-S ymmetric L ocal B inary P attern (CSLBP) feature [HPS06], E ntropy descriptor [CPW98], and optional Chain Code (CC).”
- Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics (2011, neutral): “CSLBP [25], for example, encodes in each pixel the gradient signs at the pixel in four different angles.”
- Local Trinary Patterns for human action recognition (2009, methodology): “CS-LBP [7], for example, encodes at each pixel location the sign of the gradient in four different angles.”
- Description of interest regions with local binary patterns (2009, background): “A preliminary version of this article has appeared in [25].”
- Presentation Attack Detection Methods for Face Recognition Systems (2017, methodology): “2010], and CenterSymmetric-LBP [Heikkilä et al. 2006] were also evaluated for both the photo and display screen attack in Raghavendra et al.”