The Integration of Formal and Non-formal Education: The Dutch “brede school”

The Dutch “brede school” (BS) development originates in the 1990s and has spread unevenly since: quicker in the primary than secondary educational sector. In 2007, there were about 1000 primary and 350 secondary BS schools and it is the intention of the government as well as the individual municipalities to extend that number and make the BS the dominant school form of the near future. In the primary sector, a BS cooperates with crèche and preschool facilities, besides possible other neighborhood partners. The main targets are, first, to enhance educational opportunities, particularly for children with little (western-) cultural capital, and secondly to increase women’s labor market participation by providing extra familial care for babies and small children. All primary schools are now obliged to provide such care. In the secondary sector, a BS is less neighborhood-orientated than a primary BS because those schools are bigger and more often located in different buildings. As in the primary sector, there are broad and more narrow BS, the first profile cooperating with many non-formal and other partners and facilities and the second with few. On the whole, there is a wide variety of BS schools, with different profiles and objectives, dependent on the needs and wishes of the initiators and the neighborhood. A BS is always the result of initiatives of the respective school and its partners: parents, other neighborhood associations, municipality etc. BS schools are not enforced by the government although the general trend will be that existing school organizations transform into BS. The integration of formal and non-formal education and learning is more advanced in primary than secondary schools. In secondary education, vocational as well as general, there is a clear dominance of formal education; the non-formal curriculum serves mainly two lines and objectives: first, provide attractive leisure activities and second provide compensatory courses and support for under-achievers who are often students with migrant background. In both sectors, primary and secondary, it is the formal school organization with its professionals which determines the character of a BS; there is no full integration of formal and non-formal education resulting in one non-disruptive learning trajectory, nor is there the intention to go in that direction. Non-formal pedagogues are partly professionals, like youth- and social workers, partly volunteers, like parents, partly non-educational partners, like school-police, psycho-medical help or commercial leisure providers. Besides that, the BS is regarded by government educational and social policy as a potential partner and anchor for community development. It is too early to make reliable statements about the effects of the BS movement in the Netherlands concerning the educational opportunities for disadvantaged children and their families, especially those with migrant background, and combat further segregation. Evaluation studies made so far are moderately positive but also point to problems of overly bureaucratized structures and layers, lack of sufficient financial resources and, again, are uncertain about long-term effects.

An Empirical Study of Non-Rigid Surface Feature Matching of Human from 3D Video

This paper presents an empirical study of affine invariant feature detectors to perform matching on video sequences of people with non-rigid surface deformation. Recent advances in feature detection and wide baseline matching have focused on static scenes. Video frames of human movement capture highly non-rigid deformation such as loose hair, cloth creases, skin stretching and free flowing clothing. This study evaluates the performance of six widely used feature detectors for sparse temporal correspondence on single view and multiple view video sequences. Quantitative evaluation is performed of both the number of features detected and their temporal matching against and without ground truth correspondence. Recall-accuracy analysis of feature matching is reported for temporal correspondence on single view and multiple view sequences of people with variation in clothing and movement. This analysis identifies that existing feature detection and matching algorithms are unreliable for fast movement with common clothing.

A Comparative Evaluation of Three Skin Color Detection Approaches

Skin segmentation is a challenging task due to several influences such as unknown lighting conditions, skin colored background, and camera limitations. A lot of skin segmentation approaches were proposed in the past including adaptive (in the sense of updating the skin color online) and non-adaptive approaches. In this paper, we compare three skin segmentation approaches that are promising to work well for hand tracking, which is our main motivation for this work. Hand tracking can widely be used in VR/AR e.g. navigation and object manipulation. The first skin segmentation approach is a well-known non-adaptive approach. It is based on a simple, pre-computed skin color distribution. Methods two and three adaptively estimate the skin color in each frame utilizing clustering algorithms. The second approach uses a hierarchical clustering for a simultaneous image and color space segmentation, while the third approach is a pure color space clustering, but with a more sophisticated clustering approach. For evaluation, we compared the segmentation results of the approaches against a ground truth dataset. To obtain the ground truth dataset, we labeled about 500 images captured under various conditions.