Show simple item record

dc.contributor.authorRen, Y.
dc.contributor.authorGuan, W.
dc.contributor.authorLiu, Wan-Quan
dc.contributor.authorXi, J.
dc.contributor.authorZhu, L.
dc.identifier.citationRen, Y. and Guan, W. and Liu, W. and Xi, J. and Zhu, L. 2019. Facial semantic descriptors based on information granules. Information Sciences. 479: pp. 335-354.

In this paper, we investigate a granular data description for facial components in which a characterization of facial components is presented by a collection of information granules. Firstly, the facial landmark detector is utilized to extract facial components automatically. Secondly, semantic concepts are formed by involving various mechanisms of fuzzy clustering based on these detected landmarks. A collection of numeric prototypes can be sought as a blueprint of the descriptors. Consequently, the information granules are being formed around the prototypes that are engaged by the fundamental ideas of Granular Computing, especially the principle of justifiable granularity. Multiple experiments on Multi-PIE facial database illustrate the proposed facial semantic descriptors based on information granules not only can characterize the key semantics of facial components of data, but also can improve the semantic classification performance in comparison with human perception.

dc.publisherElsevier Inc
dc.titleFacial semantic descriptors based on information granules
dc.typeJournal Article
dcterms.source.titleInformation Sciences
curtin.departmentSchool of Electrical Engineering, Computing and Mathematical Science (EECMS)
curtin.accessStatusFulltext not available

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record