CAD-model-based vision for space applications

A pose acquisition system operating in space must be able to perform well in a variety of different applications including automated guidance and inspections tasks with many different, but known objects. Since the space station is being designed with automation in mind, there will be CAD models of all the objects, including the station itself. The construction of vision models and procedures directly from the CAD models is the goal of this project. The system that is being designed and implementing must convert CAD models to vision models, predict visible features from a given view point from the vision models, construct view classes representing views of the objects, and use the view class model thus derived to rapidly determine the pose of the object from single images and/or stereo pairs

An Intuitive Graphical Query Interface for Protégé Knowledge Bases

Emily is a graphical query engine for Protégé knowledge bases that was developed by the Structural Informatics Group (SIG) at the University of Washington. Currently this application is adapted for a specific knowledge model, the Foundational Model of Anatomy (FMA) [1], but it could readily be generalized for use with other Protégé knowledge bases. In developing the Emily query interface, our intent was to provide a tool that was simple and intuitive to use, like the Queries tab provided with Protégé, but with improved information retrieval capabilities. Although some more advanced query mechanisms exist, currently they are too complicated for non-expert end users. The Algernon tab [2], for example, provides extensive Protégé query capabilities but requires users to learn a query scripting language. We sought to develop a query interface that was intuitive enough for end users to operate, with only minor instruction, yet was powerful enough to gather interesting information from a knowledge base that was not easily attained by browsing alone

An Ontology-based Image Repository for a Biomedical Research Lab

We have developed a prototype web-based database for managing images acquired during experiments in a biomedical research lab studying the factors controlling cataract development. Based on an evolving ontology we are developing for describing the experimental data and protocols used in the lab, the image repository allows lab members to organize image data by multiple attributes. The use of an ontology for developing this and other tools will facilitate intercommunication among tools, and eventual data sharing with other researchers

A STRUCTURAL MODEL OF SHAPE

Shape description and recognition is an important and interesting problem in scene analysis. Our approach to shape description is a formal model of a shape consisting of a set of primitives, their properties, and their interrelationships. The primitives are the simple parts and intrusions of the shape which can be derived through the graph-theoretic clustering procedure described in [31]. The interrelationships are two ternary relations on the primitives: the intrusion relation which relates two simple parts that join to the intrusion they surround and the protrusion relation which relates two intrusions to the protrusion between them. Using this model, a shape matching procedure that uses a tree search with look-ahead to find mappings from a prototype shape to a candidate shape has been developed. An experimental SNOBOL4 implementation has been used to test the program on hand-printed character data with favorable results

The Digital Anatomist Spatial Abstraction: A Scheme for the Spatial Description of Anatomical Features

In this paper, we propose a generalized scheme for the symbolic description of the spatial attributes of anatomical entities. The power of the scheme lies in the ability to model the spatial objects at the highest level of granularity: information can be obtained at the desired level of detail needed for a given application. This scheme uses the topological classes of point, line, surface, and volume to represent zero-D, one- D, two-D and three-D objects. A spatial object participates as a node in three complementary networks; the topology network, the part-of network, and the spatial associations network. The topology network describes a spatial object in terms of its boundaries, the part-of network describes a spatial object in terms of its parts, and the spatial associations network describes the spatial object in terms of its relationships to other spatial objects. All three of the networks can be used in combination or alone to answer queries to the spatial information system. The Digital Anatomist Structural Abstraction together with the other components of the Digital Anatomist Foundational Model1 will provide the information for describing and reasoning about anatomical entities