The ability to automatically segment a “simple” object of any size from its background is important for an active agent (e.g. a robot) to interact effectively in the real world. Recently, we proposed an algorithm [12] to segment a “simple” object in a scale invariant manner, given a point anywhere inside that object. However, in [12], a strategy to select the point inside a “simple” object was not provided. In this paper, we propose a new system that automatically selects the points inside different “simple” objects in the scene, carries out the segmentation process for the selected points, and outputs only the regions corresponding to the “simple” objects in the scene. The proposed attention mechanism for the segmentation problem utilizes, for the first time, the concept of border ownership [17].
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Visual Segmentation of Simple Objects for Robots
Semantic Scholar · Computer Science · 2011
Abstract
The ability to automatically segment a “simple” object of any size from its background is important for an active agent (e.g. a robot) to interact effectively in the real world. Recently, we proposed an algorithm [12] to segment a “simple” object in a scale invariant manner, given a point anywhere inside that object. However, in [12], a strategy to select the point inside a “simple” object was not provided. In this paper, we propose a new system that automatically selects the points inside different “simple” objects in the scene, carries out the segmentation process for the selected points, and outputs only the regions corresponding to the “simple” objects in the scene. The proposed attention mechanism for the segmentation problem utilizes, for the first time, the concept of border ownership [17].
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