| 书目名称 | Data Association for Multi-Object Visual Tracking |
| 编辑 | Margrit Betke,Zheng Wu |
| 视频video | |
| 丛书名称 | Synthesis Lectures on Computer Vision |
| 图书封面 |  |
| 描述 | .In the human quest for scientific knowledge, empirical evidence is collected by visual perception. Tracking with computer vision takes on the important role to reveal complex patterns of motion that exist in the world we live in. Multi-object tracking algorithms provide new information on how groups and individual group members move through three-dimensional space. They enable us to study in depth the relationships between individuals in moving groups. These may be interactions of pedestrians on a crowded sidewalk, living cells under a microscope, or bats emerging in large numbers from a cave. Being able to track pedestrians is important for urban planning; analysis of cell interactions supports research on biomaterial design; and the study of bat and bird flight can guide the engineering of aircraft. We were inspired by this multitude of applications to consider the crucial component needed to advance a single-object tracking system to a multi-object tracking system—data association..Data association in the most general sense is the process of matching information about newly observed objects with information that was previously observed about them. This information may be about |
| 出版日期 | Book 2017 |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-031-01816-9 |
| isbn_softcover | 978-3-031-00688-3 |
| isbn_ebook | 978-3-031-01816-9Series ISSN 2153-1056 Series E-ISSN 2153-1064 |
| issn_series | 2153-1056 |
| copyright | Springer Nature Switzerland AG 2017 |
发表于 2025-3-21 17:02:23
