Interactive object contour extraction for shape modeling

In this paper we present a semi-automatic segmentation approach suitable for extracting object contours as a precursor to 2D shape modeling. The approach is a modified and extended version of an existing state-of-the-art approach based on the concept of a Binary Partition Tree (BPT) [1]. The resulting segmentation tool facilitates quick and easy extraction of an object’s contour via a small amount of user interaction that is easy to perform, even in complicated scenes. Illustrative segmentation results are presented and the usefulness of the approach in generating object shape models is discussed.

[1]  Paulo Lobato Correia,et al.  A video object generation tool allowing friendly user interaction , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[2]  V. Michael Bove,et al.  Segmentation of an image sequence using multi-dimensional image attributes , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[3]  Noel E. O'Connor,et al.  Region-based segmentation of images using syntactic visual features , 2005 .

[4]  Rolf Adams,et al.  Seeded Region Growing , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  A Neumann,et al.  Statistical shape model based segmentation of medical images. , 1998, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[6]  Ferran Marqués,et al.  Region-based representations of image and video: segmentation tools for multimedia services , 1999, IEEE Trans. Circuits Syst. Video Technol..

[7]  John A. Marchant,et al.  Fitting grey level point distribution models to animals in scenes , 1995, Image Vis. Comput..

[8]  C. Taylor,et al.  Active shape models - 'Smart Snakes'. , 1992 .

[9]  F. Bookstein.  Landmark methods for forms without landmarks: localizing group differences in outline shape , 1996, Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.

[10]  Noel E. O'Connor,et al.  Video object segmentation for future multimedia applications , 1998 .

[11]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[12]  Fernando Pereira,et al.  Classification of video segmentation application scenarios , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[13]  Noel E. O'Connor,et al.  Efficient contour-based shape representation and matching , 2003, MIR '03.

[14]  Philippe Salembier,et al.  Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval , 2000, IEEE Trans. Image Process..