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Strong image segmentation from a data-driven perspective: impossible?

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4 Author(s)
Qiang Zhou ; Sch. of Electr. Eng. & Comput. Sci., Ohio Univ., Athens, OH, USA ; Limin Ma ; Min Zhou ; Chelberg, D.

Strong image segmentation is a very challenging problem in computer vision research. Both data-driven and model-driven approaches have been investigated in the past two decades, and many approaches proposed. Although model-based approaches are more promising in addressing strong image segmentation, data-driven approaches present more general frameworks which could potentially be adopted to segment general scenes without any prior model information. We discuss the problems of strong image segmentation from a data-driven perspective, and present a modeling technique describing an object with both its segments and a hierarchical relationship among the segments. The paper is devoted to the discussion of the feasibility of data-driven approaches for strong image segmentation. Existing approaches are not suitable for strong image segmentation in complex environments, but preliminary experimental results show the feasibility of our proposed model.

Published in:

Image Analysis and Interpretation, 2004. 6th IEEE Southwest Symposium on

Date of Conference:

28-30 March 2004