Active Visual Features Based on Events to Guide Robot Manipulators in Tracking Tasks

Traditional visual servoing systems do not deal with the topic of moving objects tracking. When these systems are employed to track a moving object, depending on the object velocity, visual features can go out of the image, causing the fail of the tracking task. This occurs specially when the object and the robot are both stopped and then the object starts the movement. In this work, we have employed a retina camera based on Address Event Representation (AER) in order to use events as input in the visual servoing system. The events launched by the camera indicate a pixel movement. Event visual information is processed only at the moment it occurs, reducing the response time of visual servoing systems when they are used to track moving objects.

City appearance and the law : a manual to assist in the development of ordinance-based visual improvement programs in smaller cities /

Includes bibliography.

Added luminance ramp alters perceived edge blur and contrast:A critical test for derivative-based models of edge coding

In many models of edge analysis in biological vision, the initial stage is a linear 2nd derivative operation. Such models predict that adding a linear luminance ramp to an edge will have no effect on the edge's appearance, since the ramp has no effect on the 2nd derivative. Our experiments did not support this prediction: adding a negative-going ramp to a positive-going edge (or vice-versa) greatly reduced the perceived blur and contrast of the edge. The effects on a fairly sharp edge were accurately predicted by a nonlinear multi-scale model of edge processing [Georgeson, M. A., May, K. A., Freeman, T. C. A., & Hesse, G. S. (in press). From filters to features: Scale-space analysis of edge and blur coding in human vision. Journal of Vision], in which a half-wave rectifier comes after the 1st derivative filter. But we also found that the ramp affected perceived blur more profoundly when the edge blur was large, and this greater effect was not predicted by the existing model. The model's fit to these data was much improved when the simple half-wave rectifier was replaced by a threshold-like transducer [May, K. A. & Georgeson, M. A. (2007). Blurred edges look faint, and faint edges look sharp: The effect of a gradient threshold in a multi-scale edge coding model. Vision Research, 47, 1705-1720.]. This modified model correctly predicted that the interaction between ramp gradient and edge scale would be much larger for blur perception than for contrast perception. In our model, the ramp narrows an internal representation of the gradient profile, leading to a reduction in perceived blur. This in turn reduces perceived contrast because estimated blur plays a role in the model's estimation of contrast. Interestingly, the model predicts that analogous effects should occur when the width of the window containing the edge is made narrower. This has already been confirmed for blur perception; here, we further support the model by showing a similar effect for contrast perception. © 2007 Elsevier Ltd. All rights reserved.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

A stable graph-based representation for object recognition through high-order matching

Many Object recognition techniques perform some flavour of point pattern matching between a model and a scene. Such points are usually selected through a feature detection algorithm that is robust to a class of image transformations and a suitable descriptor is computed over them in order to get a reliable matching. Moreover, some approaches take an additional step by casting the correspondence problem into a matching between graphs defined over feature points. The motivation is that the relational model would add more discriminative power, however the overall effectiveness strongly depends on the ability to build a graph that is stable with respect to both changes in the object appearance and spatial distribution of interest points. In fact, widely used graph-based representations, have shown to suffer some limitations, especially with respect to changes in the Euclidean organization of the feature points. In this paper we introduce a technique to build relational structures over corner points that does not depend on the spatial distribution of the features. © 2012 ICPR Org Committee.

A munkaerőpiac nemek szerinti szegregációjának jellemzői, mechanizmusa és következményei (The features, mechanism and results of gender-based segregation on the labour market)

Az ágazatok, foglalkozások, munkakörök nemek szerinti szegregációja a világ minden országára jellemző, jellegzetességei az eltérő gazdasági társadalmi, kulturális környezet ellenére gyakran nagyon hasonlítanak egymásra. Szakírók, politikai döntéshozók intézkedésekkel tartják javíthatónak a nők munkaerő-piaci pozícióját, a nemek közötti bérkülönbségek felszámolását. A követelmények és következtetések több szempontból sem helytállók. A nők és férfiak biológiai és társadalmi okokból eltérő kompetenciái, az ebből következő hatékonysági követelmények miatt a nemek szerinti elkülönülés a foglalkoztatás természetes következménye. Nem a szegregáció okozza a társadalmi egyenlőtlenségeket, hanem azok a munkaerő-piaci mechanizmusok, amelyek társadalmi hátránnyá formálják a foglalkozási struktúrában való elhelyezkedést. A beavatkozás csak ezeken keresztül lehetséges, ami azonban kockázatos, és amelynek tere meglehetősen szűk. A piaci erők önkényes korlátozása nem vezet a kívánatos eredményre, terelése csak egymással koherens társadalom-, népesség- és foglalkoztatási célrendszer megfogalmazása esetén lehet eredményes.

A projektalapú szervezetek projektmarketing-tevékenységének sajátos kontextusa (Contextual features of project marketing activity of the project-based organisations)

Ez a tanulmány a projektvezetési szakirodalomban kialakult ismeretanyagot szem előtt tartva (noha tételesen nem hivatkozva arra) tárja fel azt a sajátos és tipikusnak nevezhető kontextust, amelyben a projektalapú szervezetek projektmarketing tevékenysége megnyilvánul. A tanulmány célja tehát nem magának a projektmarketingnek a kérdéskörére irányul, hanem elsősorban annak projektspecifikus kontextusára. Jellegét illetően a tanulmány spekulatív jellegű, vagyis lényegét tekintve nem empirikus kutatási eredményekből levont következtetésekre épül. _____ Traditional approach to project marketing focuses on process-related aspects of the marketing efforts of project- based organisations. This paper is different. Unlike to the traditional approach it highlights the decisive contextual features of project marketing, bearing in mind the typical project business from the point of view of project-based organisations. These features include: a) instead of physically existing products project-based organisations need to sell their ability to create the project outcome physically; b) the project outcome and the conditions of implementation are defined by the project client; c) project clients are involved in creating the project outcome; d) project implementation strategy applied in a client organisation may vary project by project. These determining contextual features shape to a great extent the actual competitive position of the project-based organisations which may vary project by project even in relation to the very same project client.

Dynamic Distance-Based Shape Features for Gait Recognition

We propose a novel skeleton-based approach to gait recognition using our Skeleton Variance Image. The core of our approach consists of employing the screened Poisson equation to construct a family of smooth distance functions associated with a given shape. The screened Poisson distance function approximation nicely absorbs and is relatively stable to shape boundary perturbations which allows us to define a rough shape skeleton. We demonstrate how our Skeleton Variance Image is a powerful gait cycle descriptor leading to a significant improvement over the existing state of the art gait recognition rate.

Datasets, features, learning, and models in visual recognition

Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.

Crime and prejudice: The influence of appearance on blame amongst perpetrators and victims

Stereotypes based on characteristics such as age, race, and gender influence opinions in a criminal context. Yet, to date research has largely assessed whether perpetrators, rather than victims, are judged differently. Furthermore, although facial features can be a source of unconscious bias, research has failed to assess whether perceptions based on facial features affect the criminal context. To better understand the relationship between stereotypic facial features and gender, and whether this varies across perpetrators and victims, participants were asked to answer questions about an aggravated assault scenario after viewing an image of a person described as the victim or the alleged perpetrator. Images varied in gender and in presence or absence of tattoos or gothic makeup. Participants sympathized with the victim regardless of gender, but discrepancies were stronger if the victim was female than male. Neutral and tattooed faces were judged more harshly than faces with gothic makeup, regardless of gender.

Hand detection on images based on deformable part models and additional features

Hand detection on images has important applications on person activities recognition. This thesis focuses on PASCAL Visual Object Classes (VOC) system for hand detection. VOC has become a popular system for object detection, based on twenty common objects, and has been released with a successful deformable parts model in VOC2007. A hand detection on an image is made when the system gets a bounding box which overlaps with at least 50% of any ground truth bounding box for a hand on the image. The initial average precision of this detector is around 0.215 compared with a state-of-art of 0.104; however, color and frequency features for detected bounding boxes contain important information for re-scoring, and the average precision can be improved to 0.218 with these features. Results show that these features help on getting higher precision for low recall, even though the average precision is similar.

Hybrid materials based on polyethylene and MCM-41 microparticles functionalized with silanes: catalytic aspects of in situ polymerization, crystalline features and mechanical properties

New nanocomposites based on polyethylene have been prepared by in situ polymerization of ethylene in presence of mesoporous MCM-41. The polymerization reactions were performed using a zirconocene catalyst either under homogenous conditions or supported onto mesoporous MCM-41 particles, which are synthesized and decorated post-synthesis with two silanes before polymerization in order to promote an enhanced interfacial adhesion. The existence of polyethylene chains able to crystallize within the mesoporous channels in the resulting nanocomposites is figured out from the small endothermic process, located at around 80 C, on heating calorimetric experiments, in addition to the main melting endotherm. These results indicate that polyethylene macrochains can grow up during polymerization either outside or inside the MCM-41 channels, these keeping their regular hexagonal arrangements. Mechanical response is observed to be dependent on the content in mesoporous MCM-41 and on the crystalline features of polyethylene. Accordingly, stiffness increases and deformability decreases in the nanocomposites as much as MCM-41 content is enlarged and polyethylene amount within channels is raised. Ultimate mechanical performance improves with MCM-41 incorporation without varying the final processing temperature.

Comparative study of human age estimation based on hand-crafted and deep face features

In the past few years, human facial age estimation has drawn a lot of attention in the computer vision and pattern recognition communities because of its important applications in age-based image retrieval, security control and surveillance, biomet- rics, human-computer interaction (HCI) and social robotics. In connection with these investigations, estimating the age of a person from the numerical analysis of his/her face image is a relatively new topic. Also, in problems such as Image Classification the Deep Neural Networks have given the best results in some areas including age estimation. In this work we use three hand-crafted features as well as five deep features that can be obtained from pre-trained deep convolutional neural networks. We do a comparative study of the obtained age estimation results with these features.

[need For Orthodontic Treatment Among Brazilian Adolescents: Evaluation Based On Public Health].

To identify the prevalence and the severity of malocclusions and to analyze factors associated with the need for orthodontic treatment of Brazilian adolescents. This exploratory, cross-sectional study was carried out based on secondary data from the national epidemiological survey on oral health in Brazil (2002-2003). Socio-demographic conditions, self-perception, and the existence and degree of malocclusion, using the Dental Aesthetic Index, were evaluated in 16,833 adolescent Brazilians selected by probabilistic sample by conglomerates. The dependent variable - need orthodontic treatment - was estimated from the severity of malocclusion. The magnitude and direction of the association in bivariate and multivariate analyzes from a Robust Poisson regression was estimated RESULTS: The majority of the adolescents needed orthodontic treatment (53.2%). In the multivariate analysis, the prevalence of the need for orthodontic treatment was larger among females, non-whites, those that perceived a need for treatment, and those that perceived their appearance as normal, bad, or very bad. The need for orthodontic treatment was smaller among those that lived in the Northeast and Central West macro-regions compared to those living in Southeast Brazil and it was also smaller among those that perceived their chewing to be normal or their oral health to be bad or very bad. There was a high prevalence of orthodontic treatment need among adolescents in Brazil and this need was associated with demographic and subjective issues. The high prevalence of orthodontic needs in adolescents is a challenge to the goals of Brazil's universal public health system.

Late Quaternary drainage dynamics in northern Brazil based on the study of a large paleochannel from southwestern Marajó Island

Marajó Island shows an abundance of paleochannels easily mapped in its eastern portion, where vegetation consists mostly of savannas. SRTM data make possible to recognize paleochannels also in western Marajó, even considering the dense forest cover. A well preserved paleodrainage network from the adjacency of the town of Breves (southwestern Marajó Island) was investigated in this work combining remote sensing and sedimentological studies. The palimpsest drainage system consists of a large meander connected to narrower tributaries. Sedimentological studies revealed mostly sharp-based, fining upward sands for the channelized features, and interbedded muds and sands for floodplain areas. The sedimentary structures and facies successions are in perfect agreement with deposition in channelized and floodplain environments, as suggested by remote sensing mapping. The present study shows that this paleodrainage was abandoned during Late Pleistocene, slightly earlier than the Holocene paleochannel systems from the east part of the island. Integration of previous studies with the data available herein supports a tectonic origin, related to the opening of the Pará River along fault lineaments. This would explain the disappearance of large, north to northeastward migrating channel systems in southwestern Marajó Island, which were replaced by the much narrower, south to southeastward flowing modern channels.