Note: Active optical detection of cloud from a balloon platform

A disposable backscatter instrument is described for optical detection of cloud in the atmosphere from a balloon-carried platform. It uses an ultra-bright light emitting diode (LED) illumination source with a photodiode detector. Scattering of the LED light by cloud droplets generates a small optical signal which is separated from background light fluctuations using a lock-in technique. The signal to noise obtained permits cloud detection using the scattered LED light, even in daytime. The response is interpreted in terms of the equivalent visual range within the cloud. The device is lightweight (150 g) and low power (∼30 mA), for use alongside a conventional meteorological radiosonde.

Instantaneous threat detection based on a semantic representation of activities, zones and trajectories

Threat detection is a challenging problem, because threats appear in many variations and differences to normal behaviour can be very subtle. In this paper, we consider threats on a parking lot, where theft of a truck’s cargo occurs. The threats range from explicit, e.g. a person attacking the truck driver, to implicit, e.g. somebody loitering and then fiddling with the exterior of the truck in order to open it. Our goal is a system that is able to recognize a threat instantaneously as they develop. Typical observables of the threats are a person’s activity, presence in a particular zone and the trajectory. The novelty of this paper is an encoding of these threat observables in a semantic, intermediate-level representation, based on low-level visual features that have no intrinsic semantic meaning themselves. The aim of this representation was to bridge the semantic gap between the low-level tracks and motion and the higher-level notion of threats. In our experiments, we demonstrate that our semantic representation is more descriptive for threat detection than directly using low-level features. We find that a person’s activities are the most important elements of this semantic representation, followed by the person’s trajectory. The proposed threat detection system is very accurate: 96.6 % of the tracks are correctly interpreted, when considering the temporal context.

Reverse correlation reveals how observers sample visual information when estimating three-dimensional shape

Human observers exhibit large systematic distance-dependent biases when estimating the three-dimensional (3D) shape of objects defined by binocular image disparities. This has led some to question the utility of disparity as a cue to 3D shape and whether accurate estimation of 3D shape is at all possible. Others have argued that accurate perception is possible, but only with large continuous perspective transformations of an object. Using a stimulus that is known to elicit large distance-dependent perceptual bias (random dot stereograms of elliptical cylinders) we show that contrary to these findings the simple adoption of a more naturalistic viewing angle completely eliminates this bias. Using behavioural psychophysics, coupled with a novel surface-based reverse correlation methodology, we show that it is binocular edge and contour information that allows for accurate and precise perception and that observers actively exploit and sample this information when it is available.

Environmental factors and features that influence visual search in a 3D WIMP interface

The challenge of moving past the classic Window Icons Menus Pointer (WIMP) interface, i.e. by turning it ‘3D’, has resulted in much research and development. To evaluate the impact of 3D on the ‘finding a target picture in a folder’ task, we built a 3D WIMP interface that allowed the systematic manipulation of visual depth, visual aides, semantic category distribution of targets versus non-targets; and the detailed measurement of lower-level stimuli features. Across two separate experiments, one large sample web-based experiment, to understand associations, and one controlled lab environment, using eye tracking to understand user focus, we investigated how visual depth, use of visual aides, use of semantic categories, and lower-level stimuli features (i.e. contrast, colour and luminance) impact how successfully participants are able to search for, and detect, the target image. Moreover in the lab-based experiment, we captured pupillometry measurements to allow consideration of the influence of increasing cognitive load as a result of either an increasing number of items on the screen, or due to the inclusion of visual depth. Our findings showed that increasing the visible layers of depth, and inclusion of converging lines, did not impact target detection times, errors, or failure rates. Low-level features, including colour, luminance, and number of edges, did correlate with differences in target detection times, errors, and failure rates. Our results also revealed that semantic sorting algorithms significantly decreased target detection times. Increased semantic contrasts between a target and its neighbours correlated with an increase in detection errors. Finally, pupillometric data did not provide evidence of any correlation between the number of visible layers of depth and pupil size, however, using structural equation modelling, we demonstrated that cognitive load does influence detection failure rates when there is luminance contrasts between the target and its surrounding neighbours. Results suggest that WIMP interaction designers should consider stimulus-driven factors, which were shown to influence the efficiency with which a target icon can be found in a 3D WIMP interface.

Automatic attention lateral asymmetry in visual discrimination tasks

There is evidence that automatic visual attention favors the right side. This study investigated whether this lateral asymmetry interacts with the right hemisphere dominance for visual location processing and left hemisphere dominance for visual shape processing. Volunteers were tested in a location discrimination task and a shape discrimination task. The target stimuli (S2) could occur in the left or right hemifield. They were preceded by an ipsilateral, contralateral or bilateral prime stimulus (S1). The attentional effect produced by the right S1 was larger than that produced by the left S1. This lateral asymmetry was similar between the two tasks suggesting that the hemispheric asymmetries of visual mechanisms do not contribute to it. The finding that it was basically due to a longer reaction time to the left S2 than to the right S2 for the contralateral S1 condition suggests that the inhibitory component of attention is laterally asymmetric.

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.

Chaotic phase synchronization and desynchronization in an oscillator network for object selection

Object selection refers to the mechanism of extracting objects of interest while ignoring other objects and background in a given visual scene. It is a fundamental issue for many computer vision and image analysis techniques and it is still a challenging task to artificial Visual systems. Chaotic phase synchronization takes place in cases involving almost identical dynamical systems and it means that the phase difference between the systems is kept bounded over the time, while their amplitudes remain chaotic and may be uncorrelated. Instead of complete synchronization, phase synchronization is believed to be a mechanism for neural integration in brain. In this paper, an object selection model is proposed. Oscillators in the network representing the salient object in a given scene are phase synchronized, while no phase synchronization occurs for background objects. In this way, the salient object can be extracted. In this model, a shift mechanism is also introduced to change attention from one object to another. Computer simulations show that the model produces some results similar to those observed in natural vision systems.

A network of integrate and fire neurons for visual selection

Biological systems have facility to capture salient object(s) in a given scene, but it is still a difficult task to be accomplished by artificial vision systems. In this paper a visual selection mechanism based on the integrate and fire neural network is proposed. The model not only can discriminate objects in a given visual scene, but also can deliver focus of attention to the salient object. Moreover, it processes a combination of relevant features of an input scene, such as intensity, color, orientation, and the contrast of them. In comparison to other visual selection approaches, this model presents several interesting features. It is able to capture attention of objects in complex forms, including those linearly nonseparable. Moreover, computer simulations show that the model produces results similar to those observed in natural vision systems.

Detection of citrus canker in citrus plants using laser induced fluorescence spectroscopy

Citrus canker is a serious disease caused by Xanthomonas citri subsp. citri bacteria, which infects citrus plants (Citrus spp.) leading to a large economic loss in citrus production worldwide. In Brazil citrus canker control is done by an official eradication campaign, therefore early detection of such disease is important to prevent greater economic losses. However, detection is difficult and so far it has been done by visual inspection of each tree. Suspicious leaves from citrus plants in the field are sent to the laboratory to confirm the infection by laboratory analysis, which is a time consuming. Our goal was to develop a new optical technique to detect and diagnose citrus canker in citrus plants with a portable field spectrometer unit. In this paper, we review two experiments on laser induced fluorescence spectroscopy (LIF) applied to detect citrus canker. We also present new data to show that the length of time a leaf has been detached is an important variable in our studies. Our results show that LIF has the potential to be applied to citrus plants.

Objective Detection and Delineation of Oral Neoplasia Using Autofluorescence Imaging

Although the oral cavity is easily accessible to inspection, patients with oral cancer most often present at a late stage, leading to high morbidity and mortality. Autofluorescence imaging has emerged as a promising technology to aid clinicians in screening for oral neoplasia and as an aid to resection, but current approaches rely on subjective interpretation. We present a new method to objectively delineate neoplastic oral mucosa using autofluorescence imaging. Autofluorescence images were obtained from 56 patients with oral lesions and 11 normal volunteers. From these images, 276 measurements from 159 unique regions of interest (ROI) sites corresponding to normal and confirmed neoplastic areas were identified. Data from ROIs in the first 46 subjects were used to develop a simple classification algorithm based on the ratio of red-to-green fluorescence; performance of this algorithm was then validated using data from the ROIs in the last 21 subjects. This algorithm was applied to patient images to create visual disease probability maps across the field of view. Histologic sections of resected tissue were used to validate the disease probability maps. The best discrimination between neoplastic and nonneoplastic areas was obtained at 405 nm excitation; normal tissue could be discriminated from dysplasia and invasive cancer with a 95.9% sensitivity and 96.2% specificity in the training set, and with a 100% sensitivity and 91.4% specificity in the validation set. Disease probability maps qualitatively agreed with both clinical impression and histology. Autofluorescence imaging coupled with objective image analysis provided a sensitive and noninvasive tool for the detection of oral neoplasia.

Cross-situational learning of object-word mapping using Neural Modeling Fields

The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or Virtual agents have brought that issue to a central place in more applied research fields, such as computational linguistics and neural networks, as well. An attractive approach to learning an object-word mapping is the so-called cross-situational learning. This learning scenario is based on the intuitive notion that a learner can determine the meaning of a word by finding something in common across all observed uses of that word. Here we show how the deterministic Neural Modeling Fields (NMF) categorization mechanism can be used by the learner as an efficient algorithm to infer the correct object-word mapping. To achieve that we first reduce the original on-line learning problem to a batch learning problem where the inputs to the NMF mechanism are all possible object-word associations that Could be inferred from the cross-situational learning scenario. Since many of those associations are incorrect, they are considered as clutter or noise and discarded automatically by a clutter detector model included in our NMF implementation. With these two key ingredients - batch learning and clutter detection - the NMF mechanism was capable to infer perfectly the correct object-word mapping. (C) 2009 Elsevier Ltd. All rights reserved.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Ferramenta visual para especificação de hiperdocumentos, segundo o método OOHDM

O desenvolvimento de artefatos de software é um processo de engenharia, como todo processo de engenharia, envolve uma série de etapas que devem ser conduzidas através de uma metodologia apropriada. Para que um determinado software alcance seus objetivos, as características conceituais e arquiteturais devem ser bem definidas antes da implementação. Aplicações baseadas em hiperdocumentos possuem uma característica específica que é a definição de seus aspectos navegacionais. A navegação é uma etapa crítica no processo de definição de softwares baseados em hiperdocumentos, pois ela conduz o usuário durante uma sessão de visita ao conteúdo de um site. Uma falha no processo de especificação da navegação causa uma perda de contexto, desorientando o usuário no espaço da aplicação. Existem diversas metodologias para o tratamento das características de navegação de aplicações baseadas em hiperdocumentos. As principais metodologias encontradas na literatura foram estudadas e analisadas neste trabalho. Foi realizada uma análise comparativa entre as metodologias, traçando suas abordagens e etapas. O estudo das abordagens de especificação de hiperdocumentos foi uma etapa preliminar servindo como base de estudo para o objetivo deste trabalho. O foco é a construção de uma ferramenta gráfica de especificação conceitual de hiperdocumentos, segundo uma metodologia de modelagem de software baseado em hiperdocumentos. O método adotado foi o OOHDM (Object-Oriented Hypermedia Design Model), por cercar todas as etapas de um processo de desenvolvimento de aplicações, com uma atenção particular à navegação. A ferramenta implementa uma interface gráfica onde o usuário poderá modelar a aplicação através da criação de modelos. O processo de especificação compreende três modelos: modelagem conceitual, modelagem navegacional e de interface. As características da aplicação são definidas em um processo incremental, que começa na definição conceitual e finaliza nas características de interface. A ferramenta gera um protótipo da aplicação em XML. Para a apresentação das páginas em um navegador Web, utilizou-se XSLT para a conversão das informações no formato XML para HTML. Os modelos criados através das etapas de especificação abstrata da aplicação são exportados em OOHDM-ML. Um estudo de caso foi implementado para validação da ferramenta. Como principal contribuição deste trabalho, pode-se citar a construção de um ambiente gráfico de especificação abstrata de hiperdocumentos e um ambiente de implementação de protótipos e exportação de modelos. Com isso, pretende-se orientar, conduzir e disciplinar o trabalho do usuário durante o processo de especificação de aplicações.

Whole-body cortisol increases after direct and visual contact with a predator in zebrafish, Danio rerio

Ornamental fish may be severely affected by a stressful environment. Stressors impair the immune response, reproduction and growth rate; thus, the identification of possible stressors will aid to improve the overall quality of ornamental fish. The aim of this study was to determine whole-body cortisol of adult zebrafish, Danio rerio, following visual or direct contact with a predator species. Zebrafish were distributed in three groups: the first group, which consisted of zebrafish reared completely isolated of the predator, was considered the negative control; the second group, in which the predator, Parachromis managuensis was stocked together with zebrafish, was considered the positive control; the third group consisted of zebrafish stocked in a glass aquarium, with direct visual contact with the predator. The mean whole-body cortisol concentration in zebrafish from the negative control was 6.78 +/- 1.12 ng g(-1), a concentration statistically lower than that found in zebrafish having visual contact with the predator (9.26 +/- 0.88 ng g(-1)) which, in turn, was statistically lower than the mean whole-body cortisol of the positive control group (12.35 +/- 1.59 ng g(-1)). The higher whole-body cortisol concentration found in fish from the positive control can be attributed to the detection, by the zebrafish, of relevant risk situations that may involve a combination of chemical, olfactory and visual cues. One of the functions of elevated cortisol is to mobilize energy from body resources to cope with stress. The elevation of whole-body cortisol in fish subjected to visual contact with the predator involves only the visual cue in the recognition of predation risk. We hypothesized that the zebrafish could recognize predator characteristics in P managuensis, such as length, shape, color and behavior. Nonetheless, the elevation of whole-body cortisol in zebrafish suggested that the visual contact of the predator may elicit a stress response in prey fish. This assertion has a strong practical application concerning the species distribution in ornamental fish markets in which prey species should not be allowed to see predator species. Minimizing visual contact between prey and predator fish may improve the quality, viability and welfare of small fish in ornamental fish markets. (c) 2007 Elsevier B.V. All rights reserved.

Navegação cooperativa de um robô humanóide e um robô com rodas usando informação visual

This work presents a cooperative navigation systemof a humanoid robot and a wheeled robot using visual information, aiming to navigate the non-instrumented humanoid robot using information obtained from the instrumented wheeled robot. Despite the humanoid not having sensors to its navigation, it can be remotely controlled by infra-red signals. Thus, the wheeled robot can control the humanoid positioning itself behind him and, through visual information, find it and navigate it. The location of the wheeled robot is obtained merging information from odometers and from landmarks detection, using the Extended Kalman Filter. The marks are visually detected, and their features are extracted by image processing. Parameters obtained by image processing are directly used in the Extended Kalman Filter. Thus, while the wheeled robot locates and navigates the humanoid, it also simultaneously calculates its own location and maps the environment (SLAM). The navigation is done through heuristic algorithms based on errors between the actual and desired pose for each robot. The main contribution of this work was the implementation of a cooperative navigation system for two robots based on visual information, which can be extended to other robotic applications, as the ability to control robots without interfering on its hardware, or attaching communication devices