Incremental Spectral Clustering via Fastfood Features and Its Application to Stream Image Segmentation

Incremental Spectral Clustering via Fastfood Features and Its Application to Stream Image Segmentation

We propose an incremental spectral clustering method for stream data clustering and apply it to stream image segmentation. The main idea in our work consists of generating the data points in the kernel space by Fastfood features and iteratively calculating the eigendecomposition of data. Compared wi...

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Bibliographic Details
Main Authors: Li He, Yi Li, Xiang Zhang, Chuangbin Chen, Lei Zhu, Chengcai Leng
Format: Article
Language:English
Published: MDPI AG 2018-07-01
Series:Symmetry
Subjects:
symmetric kernel matrix
spectral clustering
fastfood features
Nyström approximation
pattern recognition
Online Access:http://www.mdpi.com/2073-8994/10/7/272

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http://www.mdpi.com/2073-8994/10/7/272

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