Visual Content Indexing and Retrieval with Psycho-Visual Models (eBook, PDF)

Redaktion: Benois-Pineau, Jenny; Le Callet, Patrick

• Format: PDF

Produktbeschreibung

This book provides a deep analysis and wide coverage of the very strong trend in computer vision and visual indexing and retrieval, covering such topics as incorporation of models of Human Visual attention into analysis and retrieval tasks. It makes the bridge between psycho-visual modelling of Human Visual System and the classical and most recent models in visual content indexing and retrieval.

The large spectrum of visual tasks, such as recognition of textures in static images, of actions in video content, image retrieval, different methods of visualization of images and multimedia content based on visual saliency are presented by the authors. Furthermore, the interest in visual content is modelled with the means of the latest classification models such as Deep Neural Networks is also covered in this book.

This book is an exceptional resource as a secondary text for researchers and advanced level students, who are involved in the very wide research in computer vision, visual information indexing and retrieval. Professionals working in this field will also be interested in this book as a reference.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 267
• Erscheinungstermin: 13. Oktober 2017
• Englisch
• ISBN-13: 9783319576879
• Artikelnr.: 53061162

Inhaltsangabe

Visual content indexing and retrieval with psycho-visual models.- Perceptual Texture Similarity for Machine Intelligence Applications.- Deep Saliency: Prediction of Interestingness In Video With CNN.- Introducing Image Saliency Information Into Content Based Indexing And Emotional Impact Analysis.- Saliency Prediction for Action Recognition.- Querying Multiple Simultaneous Video Streams with 3D Interest Maps.- Information theoretical model for saliency prediction. Application to Attentive CBIR.- Image retrieval based on query by saliency content.- Visual Saliency for the Visualization of Digital Paintings.- Predicting Interestingness of Visual Content.- Glossary.