书目名称 | On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities | 编辑 | Jens Spehr | 视频video | | 概述 | Provides important basic concepts, efficient methods as well as practical "how-to" examples for the use of hierarchical graphical models.Discusses the importance and the relationship between sharing a | 丛书名称 | Studies in Systems, Decision and Control | 图书封面 |  | 描述 | .In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.. | 出版日期 | Book 2015 | 关键词 | Activity Recognition; Compositional Hierarchies; Human-robot Interaction; Intelligent Vehicles Probabil | 版次 | 1 | doi | https://doi.org/10.1007/978-3-319-11325-8 | isbn_softcover | 978-3-319-35862-8 | isbn_ebook | 978-3-319-11325-8Series ISSN 2198-4182 Series E-ISSN 2198-4190 | issn_series | 2198-4182 | copyright | Springer International Publishing Switzerland 2015 |
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