Advances in Spatio-Temporal Segmentation of Visual Data

1. Auflage 2020
ISBN: 978-3-030-35482-4
Verlag: Springer International Publishing

Buch, Englisch, Band 876, 274 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 435 g

Reihe: Studies in Computational Intelligence

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. 

Zielgruppe

Research

Autoren/Hrsg.

Mashtalir, Vladimir

Levashenko, Vitaly

Ruban, Igor

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure

Inhaltsverzeichnis

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