Acogimiento en familia extensa: un estudio desde la perspectiva de los acogedores, de los niños y niñas acogidos y de los profesionales que intervienen. = Kinship foster care: a study from the perspective of the caregivers, the children and the child welfare workers

Desde hace aproximadamente dos décadas, en la mayoría de los países occidentales, los acogimientos en familia extensa han entrado a formar parte de los sistemas de protección infantil, siguiendo una evolución creciente en cuanto a número y peso especifico como recurso de acogimiento. Las investigaciones sobre este fenómeno son aún recientes y escasas como también lo son los programas dirigidos a esta población. En el presente artículo presentamos los resultados de un estudio descriptivo sobre los acogimientos en familia extensa en la ciudad de Barcelona, donde se recogen datos de los principales agentes implicados en este fenómeno. Desde la perspectiva de los estudios de la calidad de vida se analizan las percepciones, evaluaciones, y satisfacción expresada, por parte de los acogedores, los niños/as acogidos y los profesionales de los Equipos de Atención a la Infancia y Adolescencia (EAIA) que se encargan del estudio y seguimiento de estos acogimientos. La investigación presenta unos resultados acordes con los estudios que actualmente se realizan en este ámbito y sienta las bases para el despliegue futuro de programas dirigidos a los acogimientos en familia extensa

Kinship foster care: a study from the perspective of the of the caregivers, the children and the child welfare workers

In the last twenty years, in most Western countries, kinship foster care has become an integral part of childcare systems, growing progressively with regard to the numbers of children involved and relative weight as a care resource within the system; indeed, in some countries it is even more common than other placement options, such as non-kinship foster care and residential care. Research on this phenomenon is still recent and scarce, and there are few programmes targeting this population. In this article we present the results of a descriptive study on kinship foster care in the city of Barcelona, including information and data from the different stakeholders involved. From a quality of life research perspective we analyze the perceptions, evaluation and expressed satisfaction of caregivers, children and practitioners from the specialist Child and Adolescent Teams (EAIAs) responsible for the study and follow-up of kinship foster care cases. The research presented results are in line with those of current research in this field, and lays the basis for the future development of kinship foster care programmes

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

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