| 書目名稱 | Tensor Voting |
| 副標題 | A Perceptual Organiz |
| 編輯 | Philippos Mordohai,Gérard Medioni |
| 視頻video | http://file.papertrans.cn/904/903080/903080.mp4 |
| 叢書名稱 | Synthesis Lectures on Image, Video, and Multimedia Processing |
| 圖書封面 |  |
| 描述 | This lecture presents research on a general framework for perceptual organization that was conducted mainly at the Institute for Robotics and Intelligent Systems of the University of Southern California. It is not written as a historical recount of the work, since the sequence of the presentation is not in chronological order. It aims at presenting an approach to a wide range of problems in computer vision and machine learning that is data-driven, local and requires a minimal number of assumptions. The tensor voting framework combines these properties and provides a unified perceptual organization methodology applicable in situations that may seem heterogeneous initially. We show how several problems can be posed as the organization of the inputs into salient perceptual structures, which are inferred via tensor voting. The work presented here extends the original tensor voting framework with the addition of boundary inference capabilities; a novel re-formulation of the framework applicable to high-dimensional spaces and the development of algorithms for computer vision and machine learning problems. We show complete analysis for some problems, while we briefly outline our approach |
| 出版日期 | Book 2006 |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-02242-5 |
| isbn_softcover | 978-3-031-01114-6 |
| isbn_ebook | 978-3-031-02242-5Series ISSN 1559-8136 Series E-ISSN 1559-8144 |
| issn_series | 1559-8136 |
| copyright | Springer Nature Switzerland AG 2006 |
|Archiver|手機版|小黑屋|
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