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.

Data Manipulation.doc (9)

Notes on use of SPSS. Used in Research Skills for Biomedical Science

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.

Nongenetic inheritance, linguistic competence, prenatal experience and behavior manipulation: recent contributions from behavioral neurobiology and neuropsychology to the explanation of behavior

This article gives an overview of presuppositions and explanations posed by behaviorist psychology (particularly its radical branch), cognitive–nativist sciences (i.e. psycholinguistics and a branch of cognitive psychology) and other disciplines regarding important psychological events such as anxiety, stress, fear, mood states and language. In relation to the discussion of environment versus genetics, contributions from behavioral neurobiology and neuropsychology are added, showing evidence of traits that can be multigenerationally inherited in a non-genetic way, which have an impact thought the life of organisms and on their way of interacting with the environment; ways in which behavior can be altered by recently unsuspected environmental agents or events, and the overlooked role of prenatal experiences in the explanation of behavior. The evidence calls into question presuppositions made by the academic disciplines listed above, and suggests alternative behavior reinterpretations and explanations

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

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."

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." It is becoming ever more evident that museums have undergone changes that are noticeable in numerous areas. As well as the traditional functions of collecting, conserving and exhibiting objects. museums have tried to become a means of communication, open and aware of the worries of modern society. In order to do this , it has started to utilise modern technology now available and lead by the hand of "marketing" and modern business management.

Visual Object Recognition Using Deformable Models of Vehicles

This workshop paper reports recent developments to a vision system for traffic interpretation which relies extensively on the use of geometrical and scene context. Firstly, a new approach to pose refinement is reported, based on forces derived from prominent image derivatives found close to an initial hypothesis. Secondly, a parameterised vehicle model is reported, able to represent different vehicle classes. This general vehicle model has been fitted to sample data, and subjected to a Principal Component Analysis to create a deformable model of common car types having 6 parameters. We show that the new pose recovery technique is also able to operate on the PCA model, to allow the structure of an initial vehicle hypothesis to be adapted to fit the prevailing context. We report initial experiments with the model, which demonstrate significant improvements to pose recovery.

Biologically motivated model for object detection and identification in real-world scenes

The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.