Del i serien Lecture Notes in Computer Science

Computational Intelligence for Multimedia Understanding

International Workshop, MUSCLE 2011, Pisa, Italy, December 13-15, 2011, Revised Selected Papers

Häftad, Engelska, 2012

AvEmanuele Salerno,A. Enis Cetin,Ovidio Salvetti

659 kr

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The papers cover the following topics: multisensor systems, multimodal analysis, crossmodel data analysis and clustering, mixed-reality applications, activity and object detection and recognition, text and speech recognition, multimedia labelling, semantic annotation, and metadata, multimodal indexing and searching in very large data-bases;

Produktinformation

Utgivningsdatum2012-08-23
Mått155 x 235 x 14 mm
Vikt382 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor235
FörlagSpringer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN9783642324352

Tillhör följande kategorier

Grafik och bildbehandling inom Data och IT
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

Learning an Ontology for Visual Tasks.- Ontology and Algorithms Integration for Image Analysis.- EmotiWord: Affective Lexicon Creation with Application to Interaction and Multimedia Data.- A Bayesian Active Learning Framework for a Two-Class Classification Problem.- Unsupervised Classification of SAR Images Using Hierarchical Agglomeration and EM.- Geometrical and Textural Component Separation with Adaptive Scale Selection.- Bayesian Shape from Silhouettes.- Shape Retrieval and Recognition on Mobile Devices.- Directionally Selective Fractional Wavelet Transform Using a 2-D Non-separable Unbalanced Lifting Structure.- Visible and Infrared Image Registration Employing Line-Based Geometric Analysis.- Texture Recognition Using Robust Markovian Features.- A Plausible Texture Enlargement and Editing Compound Markovian Mode.- Bidirectional Texture Function Simultaneous Autoregressive Model.- Analysis of Human Gaze Interactions with Texture and Shape.- Rich Internet Application for Semi-automatic Annotation of Semantic Shots on Keyframes.- Labeling TV Stream Segments with Conditional Random Fields.- Foreground Objects Segmentation for Moving Camera Scenarios Based on SCGMM.- Real Time Image Analysis for Infomobilit.- Tracking the Saliency Features in Images Based on Human Observation Statistics.