Reference : Deformation Based Curved Shape Representation
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/31351
Deformation Based Curved Shape Representation
English
Demisse, Girum mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Aouada, Djamila mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Ottersten, Björn mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
2017
IEEE Transactions on Pattern Analysis & Machine Intelligence
IEEE
Yes (verified by ORBilu)
International
0162-8828
[en] Shape representation ; Similarity metric ; Shape matching ; Deformation
[en] In this paper, we introduce a deformation based representation space for curved shapes in Rn. Given an ordered set of points sampled from a curved shape, the proposed method represents the set as an element of a finite dimensional matrix Lie group. Variation due to scale and location are filtered in a preprocessing stage, while shapes that vary only in rotation are identified by an equivalence relationship. The use of a finite dimensional matrix Lie group leads to a similarity metric with an explicit geodesic solution. Subsequently, we discuss some of the properties of the metric and its relationship with a deformation by least action. Furthermore, invariance to reparametrization or estimation of point correspondence between shapes is formulated as an estimation of sampling function. Thereafter, two possible approaches are presented to solve the point correspondence estimation problem. Finally, we propose an adaptation of k-means clustering for shape analysis in the proposed representation space. Experimental results show that the proposed representation is robust to uninformative cues, e.g. local shape perturbation and displacement. In comparison to state of the art methods, it achieves a high precision on the Swedish and the Flavia leaf datasets and a comparable result on MPEG-7, Kimia99 and Kimia216 datasets.
Researchers
http://hdl.handle.net/10993/31351

File(s) associated to this reference

Fulltext file(s):

FileCommentaryVersionSizeAccess
Open access
DemisseAouadaOttersten_PAMI2017.pdfPublisher postprint5.56 MBView/Open

Bookmark and Share SFX Query

All documents in ORBilu are protected by a user license.