Advances in Spatio-Temporal Segmentation of Visual Data

Vladimir Mashtalir (Curatore)

Igor Ruban (Curatore)

Springer Nature Switzerland AG, 2020

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. 

• Curatore: Vladimir Mashtalir, Igor Ruban
• Editore: Springer Nature Switzerland AG
• Collana: Studies in Computational Intelligence
• Anno: 2020
• Rilegatura: Hardback
• Pagine: 274 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783030354794

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