We have been developing a theory for the generic representation of 2-D shape, where structural descriptions are derived from the shocks (singularities) of a curve evolution process, acting on bounding contours. We now apply the theory to the problem of shape matching. The shocks are organized into a directed, acyclic shock graph, and complexity is managed by attending to the most significant (central) shape components first. The space of all such graphs is highly structured and can be characterized by the rules of a shock graph grammar. The grammar permits a reduction of a shock graph to a unique rooted shock tree. We introduce a novel tree matching algorithm which finds the best set of corresponding nodes between two shock trees in polynomial time. Using a diverse database of shapes, we demonstrate our system's performance under articulation, occlusion, and changes in viewpoint. Keywords: shape representation; shape matching; shock graph; shock graph grammar; subgraph isomorphism. 1 I...

The paper is a overview of the major qualitative spatial representation and reasoning techniques. We survey the main aspects of the representation of qualitative knowledge including ontological aspects, topology, distance, orientation and shape. We also consider qualitative spatial reasoning including reasoning about spatial change. Finally there is a discussion of theoretical results and a glimpse of future work. The paper is a revised and condensed version of [33, 34].

We undertake to develop a general theory of two-dimensional shape by elucidating several principles which any such theory should meet. The principles are organized around two basic intuitions: first, if a boundary were changed only slightly, then, in general, its shape would change only slightly. This leads us to propose an operational theory of shape based on incremental contour deformations. The second intuition is that not all contours are shapes, but rather only those that can enclose "physical" material. A theory of contour deformation is derived from these principles, based on abstract conservation principles and Hamilton-Jacobi theory. These principles are based on the work of Sethian [82, 86], the Osher-Sethian level set formulation [65], the classical shock theory of Lax [53, 54], as well as curve evolution theory for a curve evolving as a function of the curvature and the relation to geometric smoothing of Gage-Hamilton-Grayson [32, 37]. The result is a characterization of th...

We present an approach for recovering surface shape from the occluding contour using an active (i.e., moving) observer. It is based onarelation between the geometries of a surface inascene and its occluding contour: If the viewing direction of the observer is along a principal direction for a surface point whose projection is on the contour, surface shape (i.e., curvature) at the surfacepoint can be recovered from the contour. Unlike previous approaches for recovering shape from the occluding contour, we use an observer that purposefully changes viewpoint in order to achieve a well-de ned geometric relationship with respect to a 3D shape prior to its recognition. We show that there is a simple and e cient viewing strategy that allows the observer to align the viewing direction with one of the two principal directions for a point on the surface. Experimental results demonstrate that our method can be easily implemented and can provide reliable shape information. 1

This paper has two objectives. First, we will argue that the mutability of conceptual fea- tures can be represented as a single, multiple-valued dimension. We will show that the fea- tures of a concept can be reliably ordered with respect to the degree to which people are willing to transform the feature while retaining the integrity of a representation; i.e., that a number of conceptual tasks, all of which require people to transform conceptual features, produce similar orderings. Following Medin and Shoben (1988), these tasks have in common that they ask people to consider an object that is missing a feature but is otherwise intact (e.g., a real chair without a seat)

Developing suitable representations for formalising non-trivial domain knowledge has always been central to AI. Within Naive Physics ie. the task of encoding experiential knowledge of the world, few formal theories have appeared that exhibit formal elegance, conciseness and generality to cover a wide variety of modelling problems. We outline a first order formalism being developed that meets these criteria. The formalism is particularly attractive in that it provides the user with the means to model either spatial and/or temporal information as required. The power of the formalism is illustrated by modelling the process of phagocytosis of the amoeba, together with an outline of how many properties of physical entities and relations between them can be modelled within a unitary framework. 1.0 Introduction The importance of representation within a formal framework has always been a central topic for discussion within AI. This has been particularly noticeable since Hayes'...

This exploratory paper quests for a stochastic and context sensitive grammar of images. The grammar should achieve the following four objectives and thus serves as a unified framework of representation, learning, and recognition for a large number of object categories. (i) The grammar represents both the hierarchical decompositions from scenes, to objects, parts, primitives and pixels by terminal and non-terminal nodes and the contexts for spatial and functional relations by horizontal links between the nodes. It formulates each object category as the set of all possible valid configurations produced by the grammar. (ii) The grammar is embodied in a simple And–Or graph representation where each Or-node points to alternative sub-configurations and an And-node is decomposed into a number of components. This representation supports recursive top-down/bottom-up procedures for image parsing under the Bayesian framework and make it convenient to scale

Several studies have shown the importance of two very different descriptors for shape: symmetry structure and curvature extrema. The main theorem proved by this paper, i.e. the Symmetry-Curvature Duality Theorem, states that there is an important relationship between symmetry and curvature extrema: If we say that curvature extrema are of two opposite types, either maxima or minima, then the theorem states: Any segment of a smooth planar curve, bounded by two consecutive curvature extrema of the same type, has a unique symmetry axis, and the axis terminates at the curvature extremum of the opposite type. The theorem is initially proved using Brady’s SLS as the symmetry analysis. However, the theorem is then generalized for any differential symmetry analysis. In order to prove the theorem, a number of results are established concerning the symmetry structure of Hoffman’s and Richards ’ codons. All results are obtained first by observing that any codon is a string of two, three, or four spirals, and then by reducing the theory of codons to that of spirals. We show that the SLS of a codon is either (1) an SAT, which is a

: Perspective projection is generally accepted as the ideal model of image formation. Many recent algorithms, and many recent judgements about the relative merits of different algorithms, depend on this assumption. However, perspective projection represents only the front half of the viewing sphere and it distorts the shape and intensity of objects unless they lie near the optical axis. It is only one of several projections used in lens design and it does not accurately model the behavior of many real lenses. It works well only for narrow-angle images. This paper surveys the properties of several alternative models of image formation. A model based on stereographic projection of the viewing sphere is shown to be a better general-purpose imaging model than perspective projection. The new model can represent wider fields of view and more closely approximates real wide-angle lenses. It preserves a suitable range of shape properties, including local symmetries. It approximates narrow-angl...

Vision should provide an explanation of the scene in terms of a causal semantics---what affects what, and why. An important part of the causal explanation of static scenes is what supports what, or, counterfactually: Why aren't things moving? We use simple naive physical knowledge as the basis of a vertically integrated vision system that explains arbitrarily complex stacked block structures. The semantics provides a basis for controlling the application of visual attention, and forms a framework for the explanation that is generated. We show how the program sequentially explores scenes of complex blocks structures, identifies functional substructures such as arches and cantilevers, and develops an explanation of why the whole construction stands and the role of each block in its stability. 1 Causal semantics for vision Much work in vision has taken as a central principle the notion that the task of vision is primarily one of explanation (e.g., [Witkin & Tanenbaum 83]). However, most...