Advances In Spatio Temporal Segmentation Of Visual Data
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Advances in Spatio-Temporal Segmentation of Visual Data
Author: Vladimir Mashtalir
language: en
Publisher: Springer Nature
Release Date: 2019-12-16
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.
Advances in Spatio-temporal Segmentation of Visual Data
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.
Advances in Visual Computing
Author: George Bebis
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-11-05
The three volume set LNCS 6453, LNCS 6454, and LNCS 6455 constitutes the refereed proceedings of the 6th International Symposium on Visual Computing, ISVC 2010, held in Las Vegas, NV, USA, in November/December 2010. The 93 revised full papers and 73 poster papers presented together with 44 full and 6 poster papers of 7 special tracks were carefully reviewed and selected from more than 300 submissions. The papers of part I (LNCS 6453) are organized in computational bioimaging, computer graphics, behavior detection and modeling, low-level color image processing, feature extraction and matching, visualization, motion and tracking, unconstrained biometrics: advances and trends, 3D mapping, modeling and surface reconstruction, and virtual reality. Part II (LNCS 6454) comprises topics such as calibration, pose estimation, and reconstruction, segmentation, stereo, registration, medical imaging, low cost virtual reality: expanding horizons, best practices in teaching visual computing, applications, and video analysis and event recognition. Part III (LNCS 6455) mainly contains papers of the poster session and concludes with contributions addressing visualization, as well as motion and tracking.