Read e-book online Advanced Concepts for Intelligent Vision Systems: 17th PDF

By Jacques Blanc-Talon, Cosimo Distante, Wilfried Philips, Dan Popescu, Paul Scheunders

ISBN-10: 3319486799

ISBN-13: 9783319486796

ISBN-10: 3319486802

ISBN-13: 9783319486802

This e-book constitutes the refereed court cases of the seventeenth foreign convention on complex innovations for clever imaginative and prescient platforms, ACIVS 2016, held in Lecce, Italy, in October 2016.
The sixty four revised complete papers provided during this quantity have been conscientiously chosen from 137 submissions. They care for classical low-level picture processing concepts; snapshot and video compression; 3D; protection and forensics; and review methodologies.

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Read or Download Advanced Concepts for Intelligent Vision Systems: 17th International Conference, ACIVS 2016, Lecce, Italy, October 24-27, 2016, Proceedings PDF

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Additional info for Advanced Concepts for Intelligent Vision Systems: 17th International Conference, ACIVS 2016, Lecce, Italy, October 24-27, 2016, Proceedings

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Fr Abstract. In this paper, we present a simple new human activity recognition method using discrete cosine transform (DCT). The scheme uses the DCT coefficients extracted from silhouettes as descriptors (features) and performs frame-by-frame recognition, which make it simple and suitable for real time applications. We carried out several tests using radial basis neural network (RBF) for classification, a comparative study against stat-of-the-art methods shows that our technique is faster, simple and gives higher accuracy performance comparing to discrete transform based techniques and other methods proposed in literature.

These segmentation contours have the same number of points, making it possible to define edges between slices to generate a face-vertex mesh. The deformable modelling process is iterative and stops when the maximum number of iterations is reached. This process consists of two components. Firstly a 2D boundary detector is carried out on each individual slice, where search paths are defined along the normal direction of each mesh vertex. A neural network is used for boundary detection in order to learn useful features, rather than spending time hand crafting them.

Retinal vessel tree segmentation using a deformable contour model. In: ICPR, pp. 2128–2131 (2008) 3. : Minimum s-excess graph for segmenting and tracking multiple borders with HMM. F. ) MICCAI 2015. LNCS, vol. 9350, pp. 28–35. Springer, Heidelberg (2015). I. Palmer and X. Xie 4. : Vessel boundary extraction based on a global and local deformable physical model with variable stiffness. MRI 16, 943–951 (1998) 5. : Interactive segmentation of mediaadventitia border in IVUS. , Smith, W. ) CAIP 2013.

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Advanced Concepts for Intelligent Vision Systems: 17th International Conference, ACIVS 2016, Lecce, Italy, October 24-27, 2016, Proceedings by Jacques Blanc-Talon, Cosimo Distante, Wilfried Philips, Dan Popescu, Paul Scheunders


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