Titlebook: Advances in Visual Computing; 6th International Sy George Bebis,Richard Boyle,Lisa Avila Conference proceedings 2010 Springer Berlin Heidel

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Incorporating Social Entropy for Crowd Behavior Detection Using SVMdetection in coherent and incoherent crowded scenes. Two main aspects describe the novelty of the proposed approach: first, modeling the observed flow field in each non-overlapping block through social entropy to measure the concerning uncertainty of underlying field. Each block serves as an indepen

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Introducing a Statistical Behavior Model into Camera-Based Fall Detection people who live alone, such a fall is a major risk. In this paper we present an approach for fall detection based on multiple cameras supported by a statistical behavior model. The model describes the spatio-temporal unexpectedness of objects in a scene and is used to verify a fall detected by a se

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outskirts

https://doi.org/10.1007/978-1-4615-6333-4d on these notions, a method is proposed for automatic segmentation of vascular structures from phase-contrast magnetic resonance angiography. Experiments performed on 16 images and validations by comparison to results obtained by two human experts emphasise the relevance of the method.

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Jianquan Lu,Jun Shen,Jinde Cao,Jürgen Kurthsse to improve the generation of reference data for the evaluation of automated segmentation algorithms. The method was designed to mimic manual cell segmentation and is based on a model of human visual perception. We demonstrate a need for automated methods to assist with the generation of reference

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Consensus on Menopause Researchegenerative diseases. Especially, morphological changes of branching patterns of dendrites and volumetric spine structure is related to cognitive functions such as experienced-based learning, attention, and memory. To quantify their morphologies, we use confocal microscopy images which enables us to