Adolfo Guzman-Arenas

Publications

• Document comparison with a weighted topic hierarchy

  A. Gelbukh, G. Sidorov, A. Guzman-Arenas

  Database and Expert Systems Applications, 1999. Proceedings. Tenth International Workshop on; 02/1999

  A method of document comparison based on a hierarchical dictionary of topics (concepts) is described. The hierarchical links in the dictionary are supplied with the weights that are used for detecting the main topics of a document and for determining the similarity between two documents. The method ... [more] A method of document comparison based on a hierarchical dictionary of topics (concepts) is described. The hierarchical links in the dictionary are supplied with the weights that are used for detecting the main topics of a document and for determining the similarity between two documents. The method allows for the comparison of documents that do not share any words literally but do share concepts, including comparison of documents in different languages. Also, the method allows for comparison with respect to a specific “aspect”, i.e., a specific topic of interest (with its respective subtopics). A system classifier using the discussed method for document classification and information retrieval is discussed

• A method of describing document contents through topic selection

  A. Gelbukh, G. Sidorov, A. Guzman-Arenas

  String Processing and Information Retrieval Symposium, 1999 and International Workshop on Groupware; 02/1999

  Given a large hierarchical dictionary of concepts, the task of selection of the concepts that describe the contents of a given document is considered. The problem consists in proper handling of the top-level concepts in the hierarchy. As a representation of the document, a histogram of the topics wi... [more] Given a large hierarchical dictionary of concepts, the task of selection of the concepts that describe the contents of a given document is considered. The problem consists in proper handling of the top-level concepts in the hierarchy. As a representation of the document, a histogram of the topics with their respective contribution in the document is used. The contribution is determined by comparison of the document with the “ideal” document for each topic in the dictionary. The “ideal” document for a concept is one that contains only the keywords belonging to this concept, in proportion to their occurrences in the training corpus. A fast algorithm of comparison for some types of metrics is proposed. The application of the method in a system classifier is discussed

• Computer Recognition of Three-Dimensional Objects in a Visual Scene

  Adolfo Guzman-Arenas

  Methods are presented (1) to partition or decompose a visual scene into the bodies forming it; (2) to position these bodies in three-dimensional space, by combining two scenes that make a stereoscopic pair; (3) to find the regions or zones of a visual scene that belong to its background; (4) to carr... [more] Methods are presented (1) to partition or decompose a visual scene into the bodies forming it; (2) to position these bodies in three-dimensional space, by combining two scenes that make a stereoscopic pair; (3) to find the regions or zones of a visual scene that belong to its background; (4) to carry out the isolation of objects in (1) when the input has inaccuracies. Running computer programs implement the methods, and many examples illustrate their behavior. The input is a two-dimensional line-drawing of the scene, assumed to contain three-dimensional bodies possessing flat faces (polyhedra); some of them may be partially occluded. Suggestions are made for extending the work to curved objects. Some comparisons are made with human visual perception. The main conclusion is that it is possible to separate a picture or scene into the constituent objects exclusively on the basis of monocular geometric properties (on the basis of pure form); in fact, successful methods are shown.

• Some Aspects of Pattern Recognition by Computer

  Adolfo Guzman-Arenas

  A computer may gather a lot of information from its environment in an optical or graphical manner. A scene, as seen for instance from a TV camera or a picture, can be transformed into a symbolic description of points and lines or surfaces. This thesis describes several programs, written in the langu... [more] A computer may gather a lot of information from its environment in an optical or graphical manner. A scene, as seen for instance from a TV camera or a picture, can be transformed into a symbolic description of points and lines or surfaces. This thesis describes several programs, written in the language CONVERT, for the analysis of such descriptions in order to recognize, differentiate and identify desired objects or classes of objects in the scene. Examples are given in each case. Although the recognition might be in terms of projections of 2-dim and 3-dim objects, we do not deal with stereoscopic information. One of our programs (Polybrick) identifies parallelepipeds in a scene which may contain partially hidden bodies and non-parallelepipedic objects. The program TD works mainly with 2-dimensional figures, although under certain conditions successfully identifies 3-dim objects. Overlapping objects are identified when they are transparent. A third program, DT, works with 3-dim and 2-dim objects, and does not identify objects which are not completely seen. Important restrictions and suppositions are: (a) the input is assumed perfect (noiseless), and in a symbolic format; (b) no perspective deformation is considered. A portion of this thesis is devoted to the study of models (symbolic representations) of the objects we want to identify; different schemes, some of them already in use, are discussed. Focusing our attention on the more general problem of identification of general objects when they substantially overlap, we propose some schemes for their recognition, and also analyze some problems that are met.