Titlebook: Computer Vision in Control Systems-2; Innovations in Pract Margarita N. Favorskaya,Lakhmi C. Jain Book 2015 Springer International Publishi

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Adaptive Surveillance Algorithms Based on the Situation Analysis,eillance algorithms, situation description, and situation analysis. The technique for generation of the descriptions of the observed scene uses the predicates and is based on the statistical methods of object recognition. Examples demonstrate the implementation of our approach in visual navigation and search of on-land mobile objects.

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Book 2015   Human Action Recognition: Contour-Based and Silhouette-based Approaches. .·         The Application of Machine Learning Techniques to Real Time Audience Analysis System. .·         Panorama Construction from Multi-view Cameras in Outdoor Scenes. .·         A New Real-Time Method of Contextual Ima

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1868-4394 digms.Presents applications and practical innovations of app.The research book is focused on the recent advances in computer vision methodologies and innovations in practice. The Contributions include:.·          Human Action Recognition: Contour-Based and Silhouette-based Approaches. .·         The

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https://doi.org/10.1007/978-94-007-7031-7reover, the classification is achieved using two classifiers: K-Nearest-Neighbor (KNN) and Support Vector Machine (SVM). The experimental results demonstrated that these features have a promising potential and useful for the human action recognition in videos.

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Stefano Filippi,Ilaria Cristofolini of global contrast (salient) objects in the STG are described, which provide the stable segmentation components for solving scene recognition problems. These algorithms are based on the geometrized histogram method developed by the author. Selection of stable segmentation components in images is ap

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Book 2015enoising Algorithms for Intelligent Recognition Systems. .·         Image Segmentation Based on Two-dimensional Markov Chains..The book is directed to the PhD students, professors, researchers and software developers working in the areas of digital video processing and computer vision technologies..

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Human Action Recognition: Contour-Based and Silhouette-Based Approaches,reover, the classification is achieved using two classifiers: K-Nearest-Neighbor (KNN) and Support Vector Machine (SVM). The experimental results demonstrated that these features have a promising potential and useful for the human action recognition in videos.

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