Towards fast and parameter-independent support vector data description for image and video segmentation
作者：
Highlights：
• A survey of kernel clustering methods is provided.
• Inspiring from the mechanism of flight guidance in particle swarm a fast kernel clustering method.
• Presenting a framework for an automatic parameter tuning for the proposed method.
• Application of the proposed method to image and video segmentation tasks.
• Developing enhancement strategies to improve image and video segmentation results.
摘要
•A survey of kernel clustering methods is provided.•Inspiring from the mechanism of flight guidance in particle swarm a fast kernel clustering method.•Presenting a framework for an automatic parameter tuning for the proposed method.•Application of the proposed method to image and video segmentation tasks.•Developing enhancement strategies to improve image and video segmentation results.
论文关键词：Support vector data description,Swarm intelligence,Unsupervised learning,Image segmentation,Video segmentation,Clustering method
论文评审过程：Received 17 September 2018, Revised 2 March 2019, Accepted 21 March 2019, Available online 23 March 2019, Version of Record 1 April 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.03.038
