Object Detection in Images by Components

In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The framework that is described here for people is easily applied to other objects as well. The motivation for developing a component based approach is two fold: first, to enhance the performance of person detection systems on frontal and rear views of people and second, to develop a framework that directly addresses the problem of detecting people who are partially occluded or whose body parts blend in with the background. The data classification is handled by several support vector machine classifiers arranged in two layers. This architecture is known as Adaptive Combination of Classifiers (ACC). The system performs very well and is capable of detecting people even when all components of a person are not found. The performance of the system is significantly better than a full body person detector designed along similar lines. This suggests that the improved performance is due to the components based approach and the ACC data classification structure.

Geometric Aspects of Visual Object Recognition

This thesis presents there important results in visual object recognition based on shape. (1) A new algorithm (RAST; Recognition by Adaptive Sudivisions of Tranformation space) is presented that has lower average-case complexity than any known recognition algorithm. (2) It is shown, both theoretically and empirically, that representing 3D objects as collections of 2D views (the "View-Based Approximation") is feasible and affects the reliability of 3D recognition systems no more than other commonly made approximations. (3) The problem of recognition in cluttered scenes is considered from a Bayesian perspective; the commonly-used "bounded-error errorsmeasure" is demonstrated to correspond to an independence assumption. It is shown that by modeling the statistical properties of real-scenes better, objects can be recognized more reliably.

Memory Usage Inference for Object-Oriented Programs

We present a type-based approach to statically derive symbolic closed-form formulae that characterize the bounds of heap memory usages of programs written in object-oriented languages. Given a program with size and alias annotations, our inference system will compute the amount of memory required by the methods to execute successfully as well as the amount of memory released when methods return. The obtained analysis results are useful for networked devices with limited computational resources as well as embedded software.

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Reusable Learning Object repository at the University of Nottingham

Over 100 RLOs in subjects relevant to health, including evidence-based practice, clinical skills, basic sciences, pharmacology, physiology, genetics and study skills.

Object Orientated PHP

To replace Application Scripting and Contemporary Programming Principles

Using the Browse Object tool in MS Word 2010

Use the Browse Object tool to quickly navigate through a selected type of object in your file – pages, tables, sections, images, footnotes or headings of your document. For best viewing Download the video.

Using the Browse Object tool in MS Word 2011

Use the Browse Object tool to quickly navigate through a selected type of object in your file – pages, tables, sections, images, footnotes or headings of your document. For best viewing Download the video.

Development and/or change of the notion of permanent object and operative causality: empirical evidence in the first year of life

This study examines the notion of permanent object during the first year of life, taking into account the controversy of two approaches about the nature of change: developmental change and cognitive change. Using a longitudinal/cross-sectional design, tasks adapted of the subscale of permanent object and operative causality of the Uzgiris-Hunt Scale (Uzgiris and Hunt, 1975) (Uzgiris & Hunt, 1975) were presented to 110 infants of 0, 3, 6 and 9 months-old, which reside in three cities of Colombia. The results showed three types of strategies: (a) Not resolution; (b) Exploratory and (c) Resolution, which follow different trajectories in children’s performance. This allows affirming that adaptive conquests of the cognitive development stay together with the variety of strategies. Using strategies reveals adjustments and transformations of action programs that consolidate the notion of permanent object not necessarily with age, but with self-regulatory processes. Empirical evidence contributes to the understanding of the relations between the emergence of novelty in the development and performance variability

Estética del rock

El objetivo del presente artículo es el de analizar la estética del Rock en términos de la experiencia que ofrece este género musical. En primer lugar se construirá una relación entre el Nacimiento de la tragedia de Nietzsche y el surgimiento del Rock, bajo la premisa de que el origen del Rock es eminentemente dionisíaco; luego se mostrará una forma de la experiencia en la vida cotidiana de quien escucha Rock, en donde se da cuenta de la necesidad de expresar los sentimientos de placer y displacer en el individuo; por último, se verá el concierto como expresión última del Rock, expresión que se enmarca dentro de la característica de una celebración-ritual que guarda semejanzas con la tragedia griega. Estos elementos terminan por dar cuenta de una forma de ver el mundo en la que se constituye la individualidad dentro de la comunidad electiva

Audiobooks : improving fluency and instilling literary skills and education for development

Resumen basado en el de la publicaci??n. Resumen en espa??ol

Image classification for a large number of object categories

L'increment de bases de dades que cada vegada contenen imatges més difícils i amb un nombre més elevat de categories, està forçant el desenvolupament de tècniques de representació d'imatges que siguin discriminatives quan es vol treballar amb múltiples classes i d'algorismes que siguin eficients en l'aprenentatge i classificació. Aquesta tesi explora el problema de classificar les imatges segons l'objecte que contenen quan es disposa d'un gran nombre de categories. Primerament s'investiga com un sistema híbrid format per un model generatiu i un model discriminatiu pot beneficiar la tasca de classificació d'imatges on el nivell d'anotació humà sigui mínim. Per aquesta tasca introduïm un nou vocabulari utilitzant una representació densa de descriptors color-SIFT, i desprès s'investiga com els diferents paràmetres afecten la classificació final. Tot seguit es proposa un mètode par tal d'incorporar informació espacial amb el sistema híbrid, mostrant que la informació de context es de gran ajuda per la classificació d'imatges. Desprès introduïm un nou descriptor de forma que representa la imatge segons la seva forma local i la seva forma espacial, tot junt amb un kernel que incorpora aquesta informació espacial en forma piramidal. La forma es representada per un vector compacte obtenint un descriptor molt adequat per ésser utilitzat amb algorismes d'aprenentatge amb kernels. Els experiments realitzats postren que aquesta informació de forma te uns resultats semblants (i a vegades millors) als descriptors basats en aparença. També s'investiga com diferents característiques es poden combinar per ésser utilitzades en la classificació d'imatges i es mostra com el descriptor de forma proposat juntament amb un descriptor d'aparença millora substancialment la classificació. Finalment es descriu un algoritme que detecta les regions d'interès automàticament durant l'entrenament i la classificació. Això proporciona un mètode per inhibir el fons de la imatge i afegeix invariança a la posició dels objectes dins les imatges. S'ensenya que la forma i l'aparença sobre aquesta regió d'interès i utilitzant els classificadors random forests millora la classificació i el temps computacional. Es comparen els postres resultats amb resultats de la literatura utilitzant les mateixes bases de dades que els autors Aixa com els mateixos protocols d'aprenentatge i classificació. Es veu com totes les innovacions introduïdes incrementen la classificació final de les imatges.

The construction of the museological object

"Exhibiting is or should be to work against ignorance, especially against the most refractory of all ignorance: the pre-conceived idea of stereo typed culture. To exhibit is to take a calculated risk of disorientation - in the etymological sense : ( to lose your bearings), disturbs the harmony, the evident , and the consensus, that constitutes the common place ( the banal). Needless to say however it is obvious that an exhibition that deliberately tries to scandalise will create an inverted perversion which results in an obscurantist pseudo-luxury - culture ... between demagogy and provocation, one has to find visual communication's subtle itinerary. Even though an intermediary route is not so stimulating : as Gaston Bachelard said "All the roads lead to Rome, except the roads of compromise."