287 resultados para action segmentation


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Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.

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The performance of iris recognition systems is significantly affected by the segmentation accuracy, especially in non- ideal iris images. This paper proposes an improved method to localise non-circular iris images quickly and accurately. Shrinking and expanding active contour methods are consolidated when localising inner and outer iris boundaries. First, the pupil region is roughly estimated based on histogram thresholding and morphological operations. There- after, a shrinking active contour model is used to precisely locate the inner iris boundary. Finally, the estimated inner iris boundary is used as an initial contour for an expanding active contour scheme to find the outer iris boundary. The proposed scheme is robust in finding exact the iris boundaries of non-circular and off-angle irises. In addition, occlusions of the iris images from eyelids and eyelashes are automatically excluded from the detected iris region. Experimental results on CASIA v3.0 iris databases indicate the accuracy of proposed technique.

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The global financial crisis, global pandemics, global warming and peak oil are indicative of a world facing major environmental, social and economic problems. At the same time, world population continues to rise and global inequalities deepen. Children are the most vulnerable to the impacts of unsustainable living with specific harms arising because of their physical and cognitive vulnerabilities. Nevertheless, children do not have to be victims in the face of these challenges. Education, including early childhood education, has an important role to in building resilience and capabilities in children that equip them as active and informed citizens now and in the future and who are capable of contributing to healthy and sustainable ways of living. Drawing on educational change literature, action research, education for sustainability, health promotion and systems theory, this paper outlines three strategies that can help reorient early childhood education towards sustainability. One strategy is the adoption of whole centre approaches to sustainability and education for sustainability. This means working across the whole of a centre’s operations – curriculum and pedagogy, physical and social environments, its partnerships and community connections. The second strategy – applied in conjunction with the first – is the use of action research to investigate the early childhood setting and to create the desired changes. The third strategy is the adoption of systems thinking as a way of leveraging support and momentum for change so that education for sustainability goes beyond the initiatives of individual teachers and centres, and becomes a systems-wide imperative.

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Silhouettes are common features used by many applications in computer vision. For many of these algorithms to perform optimally, accurately segmenting the objects of interest from the background to extract the silhouettes is essential. Motion segmentation is a popular technique to segment moving objects from the background, however such algorithms can be prone to poor segmentation, particularly in noisy or low contrast conditions. In this paper, the work of [3] combining motion detection with graph cuts, is extended into two novel implementations that aim to allow greater uncertainty in the output of the motion segmentation, providing a less restricted input to the graph cut algorithm. The proposed algorithms are evaluated on a portion of the ETISEO dataset using hand segmented ground truth data, and an improvement in performance over the motion segmentation alone and the baseline system of [3] is shown.

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This manual is designed to assist human service practitioners and agencies, and the communities they work with, to enhance their skills in undertaking Participatory Action Research, and, in so doing improve the situations of people who are vulnerable. It utilises insights derived from a number of Australian Government funded programs, most notably Reconnect, NAYSS and Household Organisational Management Expenses (HOME) Advice.

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The diversity of community voices in the SEQ ‘bellwether region’ has grown from a muted murmur in the mid twentieth century supporting provision of urban services, rural conservation and green belts, to the current clamour against over-development, and in favour of protecting local and regional open space, wetlands and natural habitats. This in turn has often resulted in vigorous campaigns against unpopular roads, dams, dumps and tall buildings. In the last twenty years community issues have played a major part in local government elections throughout the region and have even helped unseat (in 1995-1996) a state government which discounted their authenticity and community resolve.