Managing Industrial Simulator Visual Databases Using Geographic Information Systems

Geographic Information Systems are developed to handle enormous volumes of data and are equipped with numerous functionalities intended to capture, store, edit, organise, process and analyse or represent the geographically referenced information. On the other hand, industrial simulators for driver training are real-time applications that require a virtual environment, either geospecific, geogeneric or a combination of the two, over which the simulation programs will be run. In the final instance, this environment constitutes a geographic location with its specific characteristics of geometry, appearance, functionality, topography, etc. The set of elements that enables the virtual simulation environment to be created and in which the simulator user can move, is usually called the Visual Database (VDB). The main idea behind the work being developed approaches a topic that is of major interest in the field of industrial training simulators, which is the problem of analysing, structuring and describing the virtual environments to be used in large driving simulators. This paper sets out a methodology that uses the capabilities and benefits of Geographic Information Systems for organising, optimising and managing the visual Database of the simulator and for generally enhancing the quality and performance of the simulator.

Direct mesh: A multiresolution approach to terrain visualization

Terrain can be approximated by a triangular mesh consisting millions of 3D points. Multiresolution triangular mesh (MTM) structures are designed to support applications that use terrain data at variable levels of detail (LOD). Typically, an MTM adopts a tree structure where a parent node represents a lower-resolution approximation of its descendants. Given a region of interest (ROI) and a LOD, the process of retrieving the required terrain data from the database is to traverse the MTM tree from the root to reach all the nodes satisfying the ROI and LOD conditions. This process, while being commonly used for multiresolution terrain visualization, is inefficient as either a large number of sequential I/O operations or fetching a large amount of extraneous data is incurred. Various spatial indexes have been proposed in the past to address this problem, however level-by-level tree traversal remains a common practice in order to obtain topological information among the retrieved terrain data. A new MTM data structure called direct mesh is proposed. We demonstrate that with direct mesh the amount of data retrieval can be substantially reduced. Comparing with existing MTM indexing methods, a significant performance improvement has been observed for real-life terrain data.

Context-aware visual exploration of molecular databases

Facilitating the visual exploration of scientific data has received increasing attention in the past decade or so. Especially in life science related application areas the amount of available data has grown at a breath taking pace. In this paper we describe an approach that allows for visual inspection of large collections of molecular compounds. In contrast to classical visualizations of such spaces we incorporate a specific focus of analysis, for example the outcome of a biological experiment such as high throughout screening results. The presented method uses this experimental data to select molecular fragments of the underlying molecules that have interesting properties and uses the resulting space to generate a two dimensional map based on a singular value decomposition algorithm and a self organizing map. Experiments on real datasets show that the resulting visual landscape groups molecules of similar chemical properties in densely connected regions.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

Physical Activity Interventions For Children And Youth With Visual Impairments.

The authors conducted a systematic literature review on physical activity interventions for children and youth with visual impairment (VI). Five databases were searched to identify studies involving the population of interest and physical activity practices. After evaluating 2,495 records, the authors found 18 original full-text studies published in English they considered eligible. They identified 8 structured exercise-training studies that yielded overall positive effect on physical-fitness and motor-skill outcomes. Five leisure-time-physical-activity and 5 instructional-strategy interventions were also found with promising proposals to engage and instruct children and youth with VI to lead an active lifestyle. However, the current research on physical activity interventions for children and youth with VI is still limited by an absence of high-quality research designs, low sample sizes, use of nonvalidated outcome measures, and lack of generalizability, which need to be addressed in future studies.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Visual Customer Segmentation and Data Exploration with the Self-Organizing Map

Advancements in information technology have made it possible for organizations to gather and store vast amounts of data of their customers. Information stored in databases can be highly valuable for organizations. However, analyzing large databases has proven to be difficult in practice. For companies in the retail industry, customer intelligence can be used to identify profitable customers, their characteristics, and behavior. By clustering customers into homogeneous groups, companies can more effectively manage their customer base and target profitable customer segments. This thesis will study the use of the self-organizing map (SOM) as a method for analyzing large customer datasets, clustering customers, and discovering information about customer behavior. Aim of the thesis is to find out whether the SOM could be a practical tool for retail companies to analyze their customer data.

Visual analysis of image collections

Multidimensional Visualization techniques are invaluable tools for analysis of structured and unstructured data with variable dimensionality. This paper introduces PEx-Image-Projection Explorer for Images-a tool aimed at supporting analysis of image collections. The tool supports a methodology that employs interactive visualizations to aid user-driven feature detection and classification tasks, thus offering improved analysis and exploration capabilities. The visual mappings employ similarity-based multidimensional projections and point placement to layout the data on a plane for visual exploration. In addition to its application to image databases, we also illustrate how the proposed approach can be successfully employed in simultaneous analysis of different data types, such as text and images, offering a common visual representation for data expressed in different modalities.

O papel dos sistemas visual, vestibular, somatosensorial e auditivo para o controle postural

The maintenance of a given body orientation is obtained by the complex relation between sensory information and muscle activity. Therefore, this study purpose was to review the role of visual, somatosensory, vestibular and auditory information in the maintenance and control of the posture. Method. a search by papers for the last 24 years was done in the PubMed and CAPES databases. The following keywords were used: postural control, sensory information, vestibular system, visual system, somatosensory system, auditory system and haptic system. Results. the influence of each sensory system and its integration were analyzed for the maintenance and control of the posture. Conclusion. the literature showed that there is information redundancy provided by sensory channels. Thus, the central nervous system chooses the main source for the posture control.

Estratégias de ensino e recursos pedagógicos para o ensino do aluno com deficiência visual na atividade física adaptada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

On-line adaptive visual tracking

Visual tracking is the problem of estimating some variables related to a target given a video sequence depicting the target. Visual tracking is key to the automation of many tasks, such as visual surveillance, robot or vehicle autonomous navigation, automatic video indexing in multimedia databases. Despite many years of research, long term tracking in real world scenarios for generic targets is still unaccomplished. The main contribution of this thesis is the definition of effective algorithms that can foster a general solution to visual tracking by letting the tracker adapt to mutating working conditions. In particular, we propose to adapt two crucial components of visual trackers: the transition model and the appearance model. The less general but widespread case of tracking from a static camera is also considered and a novel change detection algorithm robust to sudden illumination changes is proposed. Based on this, a principled adaptive framework to model the interaction between Bayesian change detection and recursive Bayesian trackers is introduced. Finally, the problem of automatic tracker initialization is considered. In particular, a novel solution for categorization of 3D data is presented. The novel category recognition algorithm is based on a novel 3D descriptors that is shown to achieve state of the art performances in several applications of surface matching.

Visual disturbance following sclerotherapy for varicose veins, reticular veins and telangiectasias: a systematic literature review

The objective of the study was to review the literature reporting visual disturbance (VD) following sclerotherapy for varicose veins. Underlying mechanisms will be discussed. A literature search of the databases Medline and Google Scholar was performed. Original articles including randomized trials, case series and case reports reporting VD in humans following sclerotherapy for varicose veins were included. Additional references were also obtained if they had been referenced in related publications. The search yielded 4948 results of which 25 reports were found to meet the inclusion criteria. In larger series with at least 500 included patients the prevalence of VD following sclerotherapy ranges from 0.09% to 2%. In most reports foam sclerotherapy was associated with VD (19); exclusive use of liquid sclerosant was reported in two cases, some reports included foam and liquid sclerosant (4). There were no persistent visual disorders reported. VD occurred with polidocanol and sodium tetradecyl sulphate in different concentrations (0.25-3%). Various forms of foam preparation including various ways of foam production and the liquid - air ratio (1 or 2 parts of liquid mixed with 3, 4 or 5 parts of air) were reported in association with the occurrence of VD. VDs following sclerotherapy for varicose veins are rare and all reported events were transient. Bubble embolism or any kind of embolism seems unlikely to be the only underlying mechanism. A systemic inflammatory response following sclerotherapy has been suggested. Further research to clarify the mechanism of action of sclerosants is required.

Visual disturbance following sclerotherapy for varicose veins, reticular veins and telangiectasias: a systematic literature review.

The objective of the study was to review the literature reporting visual disturbance (VD)following sclerotherapy for varicose veins. Underlying mechanisms will be discussed. A literature search of the databases Medline and Google Scholar was performed. Original articles including randomized trials, case series and case reports reporting VD in humans following sclerotherapy for varicose veins were included. Additional references were also obtained if they had been referenced in related publications. The search yielded 4948 results of which 25 reports were found to meet the inclusion criteria. In larger series with at least 500 included patients the prevalence of VD following sclerotherapy ranges from 0.09% to 2%. In most reports foam sclerotherapy was associated with VD (19); exclusive use of liquid sclerosant was reported in two cases, some reports included foam and liquid sclerosant (4). There were no persistent visual disorders reported. VD occurred with polidocanol and sodium tetradecyl sulphate in different concentrations (0.25–3%). Various forms of foam preparation including various ways of foam production and the liquid –air ratio (1 or 2 parts of liquid mixed with 3, 4 or 5 parts of air) were reported in association with the occurrence of VD. VDs following sclerotherapy for varicose veins are rare and all reported events were transient. Bubble embolism or any kind of embolism seems unlikely to be the only underlying mechanism. A systemic inflammatory response following sclerotherapy has been suggested. Further research to clarify the mechanism of action of sclerosants is required.

Real-Time Adaptive Multi-Classifier Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles

This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.