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An integrated approach for object shape registration and modeling

Adamek, Tomasz and O'Connor, Noel E. and Jones, Gareth J.F. and Murphy, Noel (2005) An integrated approach for object shape registration and modeling. In: MIR 2005 - 7th ACM SIGMM international Workshop on Multimedia Information Retrieval, 15 - 19 August 2005, Salvador, Brazil.

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Abstract

In this paper, an integrated approach to fast and efficient construction of statistical shape models is proposed that is a potentially useful tool in Information Retrieval(IR). The tool allows intuitive extraction of accurate contour examples from a set of images using a semi-automatic segmentation approach. The user is allowed to draw on the scene by simply dragging a mouse over the image and creating a set of labelled scribbles for the objects to be segmented. An automatic segmentation algorithm uses the scribbles to partition the scene and extract objects’ contour. A set of labelled points (landmarks) is identified automatically on the set of examples thereby allowing statistical modeling of the objects’ shape. The main contribution of this paper is the new approach to automatic landmark identification eliminating the burden of manual landmarking. The approach utilizes a robust method for pairwise correspondence proposed originally in [1, 2]. The landmarks are used to train statistical shape models known as Point Distribution Models (PDM) [11]. Qualitative results are presented for 3 classes of shape which exhibit various types of nonrigid deformation.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Additional Information:Workshop held in conjunction with the 28th annual ACM SIGIR conference on Information Retrieval, Salvador Brazil, 15-19 August 2005
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Official URL:http://mmir.doc.ic.ac.uk/mmir2005/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Enterprise Ireland, Science Foundation Ireland, SFI 03/IN.3/I361
ID Code:384
Deposited On:31 Mar 2008 by DORAS Administrator. Last Modified 05 May 2010 16:38

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