This paper proposes a novel methodology for generating 3D point clouds of good accuracy from stereo pairs RGB images. Initially, the methodology defines some conditions for the proper selection of image pairs. Then, the selected stereo images are used to estimate dense correspondences using the Daisy descriptor. An efficient two-phase strategy to remove outliers is then introduced. Finally, the 3D point cloud is refined by combining sub-pixel accuracy correspondences estimation and the moving least squares algorithm. The proposed methodology can be exploited by multi-view stereo algorithms due to its good accuracy and its fast computation.

3D facade modeling consists of representing architectural elements of a building in detail so that both geometry and appearance are generated in a photo-realistic 3D scene. In this article, we review four main techniques used to solve this problem: photogrammetry, sparse and dense reconstruction based on SfM (Structure from Motion) and procedural modeling. We provide a comparison of several methods in these categories by considering their main advantages and limitations.

We propose a methodology inspired by Gestalt laws to extract and combine features and we test it on the object category recognition problem. Gestalt is a psycho-visual theory of Perceptual Organization that aims to explain how visual information is organized by our brain. We interpreted its laws of homogeneity and continuation in link with shape and color to devise new features beyond the classical proximity and similarity laws. The shape of the object is analyzed based on its skeleton (good continuation) and as a measure of homogeneity, we propose self-similarity enclosed within shape computed at super-pixel level. Furthermore, we propose a framework to combine these features in different ways and we test it on Caltech 101 database. The results are good and show that such an approach improves objectively the efficiency in the task of object category recognition.

This paper presents an Intelligent Tutoring System (ITS) applied to the teaching of anatomy of the female breast, including some types of cancer related to this organ. This ITS is composed of four modules: Student, an Expert System containing a questionnaire for the diagnosis of the learner’s profile; Tutor, an Artificial Neural Network Interactive Activation and Competition, for the application of teaching techniques; Domain, some ontologies containing content and related media; and Interface, developed as an Adaptive Hypermedia System. The objective of this work is to lift requirements for the integration of various modeling types that use Artificial Intelligence techniques in the same ITS, even enabling the use of this system in a Medical Simulation Environment. The validation process of this ITS is in progress because the class period has not yet started at three universities: the University of Brasilia (Federal) and the Catholic University of Brasília (Private), both located in Brasilia, Brazil, and the Universidad de La Frontera (Federal) located in Temuco, Chile.

Recognition of human faces has been a fascinating subject in research field for many years. It is considered a multidisciplinary field because includes understanding different domains such as psychology, neuroscience, computer vision, artificial intelligence, mathematics and many others. Human face perception is intriguing and draws our attention because we accomplish the task so well that we hope one day witnessing a machine performing the same task in a similar or better way. This chapter aims to provide a systematic and practical approach regarding to one of the most current techniques applied on face recognition, known as AAM (Active Appearance Model). AAM method will be addressed considering 2D face processing only.  This chapter doesn’t cover the entire theme, but offers to the reader the necessary tools to construct a consistent and productive pathway toward this involving subject.

Our perception about the word is so deeply ingrained in our day life experiences that we never stop to ask ourselves how all the pieces of visual information are organized in large and small units in order to give birth to the things we so much appreciate in our world. This is the problem addressed by perceptual organization originated with the Gestalt psychologist in 1935. Nowadays it is also a problem of interest of Computer Vision practitioners which aim to building system which perceive and understand the world. In this work we propose a new method for extracting features from images, inspired in the Gestalt laws and for the purpose of object categorization. Our main interest is to provide an organization of visual information in higher semantical levels and test its eciency in the categorization problem. Most of the work in this area consider feature extraction on the pixel-level and applying the Gestalt laws of proximity and similarity only. Our approach extends this idea by considering other Gestalt principles and adding new features in order to capture not only semantic information about the shape of the object, but also regarding its appearance.

The science of ontology has been widely used in knowledge management, either to define and organize concepts for the purpose of future preservation or to provide more efficient information processing by our computers. From this, the use of ontology in medical field has become increasingly consolidated, either to simply describe the correct meaning of technical terms or to completely depict the anatomical structure of the human body or medical procedures. In addition, the use of ontology has been associated to artificial intelligence and virtual reality in order to provide simulation of medical environments with the aim of better understand the complexities of the human anatomy and the medical procedures. Accordingly, this article presents the elaboration of an ontology and a 3D graphic model of the female breast anatomy to be used in a virtual reality environment containing an intelligent tutor system which will eventually be able to assist learners in the practice of the core needle biopsy. This article reports our experience so as to share information about the process used, the artifacts generated and the systematic involved in the structuring of such unified model.

The ontology has been widely used in knowledge management, either with a view to defining and organizing concepts in order to preserve it for future generations or to allow for a more efficient processing of information by computers. This paper presents the elaboration process of an ontology to describe the anatomy of the female breast to be used in a virtual reality environment containing an intelligent tutor system that will eventually be able to assist learners in the practice of core needle biopsy.

Technical report about e-Government interoperability that presents technical requirements and suggests use of technologies and standards with the objective of promoting system integration and better quality on the development of e-Gov solutions.

Technical report about e-Government interoperability under the point of view of an IT Manager who works on the development of solutions for the Brazilian Government.

The transition from Mammography based on films to Digital Mammography or FFDM (Full-field Digital Mammography) is not a simple task, involving solely the replacement of a few electronic components and the addition of new computers and software. This paper describes a process for integrating RIS (Radiology Information Systems), PACS (Picture Archiving and Communications Systems) and digital mammography equipments in order to help clinical engineers and IT professionals in planning, preparation and implementation of a FFDM environment in conformity with the data communication standards used in the medicine field.

This work offers a study involving the integration between RIS (Radiology Information Systems), PACS (Picturing Archiving and Communications Systems) and digital mammography equipments aiming at helping clinical engineers and IT professionals in the planning, preparation and implementation of an FFDM (Full-field Digital Mammography) environment in conformity with the data communication standards used in the medicine field nowadays and, more specifically, in the digital mammography practice.

This work provides a practical guide for requirement engineering which comprises the following processes: preparation for requirement management, problem identification and analysis, understanding users need, defining the problem, scope management, requirements refinement and managing requirements change.

The rise in the use of Web Services imposes the need to create new mechanisms to describe and store information about the services offered and their providers. Such information should be part of a centralised or federated catalogue, whose main goal would be to document the offered services on a patterned fashion, making searches easier and enabling their proper management (i.e. policy management, service level agreements, pricing and charge-back models). This dissertation provides a study about Services Oriented Architecture (SOA) and the use of Web Services technology. A meta-data model denominated XRIM-WS was created based on the ebXML-RIM standard, as to provide a detailed and conceptual specification to develop a register/repository of Web Services.

This paper depicts the Referential Architecture (AR) – the Brazilian Government initiative on SOA. AR uses the Electronic Government Interoperability Standards (e-PING) as a guide to implement technological IT standards. Within a logical and physical view, AR includes a QoS3 model to be applied on real service-based governmental projects. It also details a case study of AR to illustrate the operation and applicability of such model.