NDLI: Optimisation for image salient object detection based on semantic-aware clustering and CRF

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Optimisation for image salient object detection based on semantic-aware clustering and CRF

Content Provider	IET Digital Library
Author	Chen, Junhao Niu, Yuzhe Wu, Jianbin Chen, Junrong
Abstract	State-of-the-art optimisation methods for salient object detection neglect that saliency maps of different images usually show different imperfections. Therefore, the saliency maps of some images cannot achieve effective optimisation. Based on the observation that the saliency maps of semantically similar images usually show similar imperfections, the authors propose an optimisation method for salient object detection based on semantic-aware clustering and conditional random field (CRF), named CCRF. They first cluster the training images into some clusters using the image semantic features extracted by using a deep convolutional neural network model for image classification. Then for each cluster, they use a CRF to optimise the saliency maps generated by existing salient object detection methods. A grid search method is used to compute the optimal weights of the kernels of the CRF. The saliency maps of the testing images are optimised by the corresponding CRFs with the optimal weights. The experimental results with 13 typical salient object detection methods on four datasets show that the proposed CCRF algorithm can effectively improve the results of a variety of image salient object detection methods and outperforms the compared optimisation methods.
Starting Page	49
Ending Page	58
Page Count	10
ISSN	17519632
Volume Number	14
e-ISSN	17519640
Issue Number	Issue 2, Mar (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/14/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2019.0063
Journal	IET Computer Vision
Publisher Date	2019-10-14
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique CRF Different Imperfections Feature Extraction Grid Search Method Image Classification Image Recognition Image Salient Object Detection Image Semantic Feature Neural Nets Object Detection Object Detection Method Optimisation Optimisation Method Optimisation Technique Pattern Clustering Saliency Maps Salient Object Detection Neglect Semantic-aware Clustering Semantically Similar Image Training Image
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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