Advances in Spatio-Temporal Segmentation of Visual Data (eBook, PDF)

Redaktion: Mashtalir, Vladimir; Levashenko, Vitaly; Ruban, Igor

• Format: PDF

Produktbeschreibung

This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval. The main focus is on the spatio-temporal segmentation of visual information.

Sets of meaningful and manageable image or video parts, defined by visual interest or attention to higher-level semantic issues, are often vital to the efficient and effective processing and interpretation of viewable information. Developing robust methods for spatial and temporal partition represents a key challenge in computer vision and computational intelligence as a whole.

This book is intended for students and researchers in the fields of machine learning and artificial intelligence, especially those whose work involves image processing and recognition, video parsing, and content-based image/video retrieval.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 274
• Erscheinungstermin: 16. Dezember 2019
• Englisch
• ISBN-13: 9783030354800
• Artikelnr.: 58430523

Inhaltsangabe

Adaptive Edge Detection Models and Algorithms.- Swarm Methods of Image Segmentation.- Spatio-temporal Data Interpretation Based on Perceptional Model.- Spatio-Temporal Video Segmentation.