Curved Inertia Frames: Visual Attention and Perceptual Organization Using Convexity and Symmetry

In this paper we present an approach to perceptual organization and attention based on Curved Inertia Frames (C.I.F.), a novel definition of "curved axis of inertia'' tolerant to noisy and spurious data. The definition is useful because it can find frames that correspond to large, smooth, convex, symmetric and central parts. It is novel because it is global and can detect curved axes. We discuss briefly the relation to human perception, the recognition of non-rigid objects, shape description, and extensions to finding "features", inside/outside relations, and long- smooth ridges in arbitrary surfaces.

Perceptual Organization, Figure-Ground, Attention and Saliency

Notions of figure-ground, inside-outside are difficult to define in a computational sense, yet seem intuitively meaningful. We propose that "figure" is an attention-directed region of visual information processing, and has a non-discrete boundary. Associated with "figure" is a coordinate frame and a "frame curve" which helps initiate the shape recognition process by selecting and grouping convex image chunks for later matching- to-model. We show that human perception is biased to see chunks outside the frame as more salient than those inside. Specific tasks, however, can reverse this bias. Near/far, top/bottom and expansion/contraction also behave similarly.