The World of Fast Moving Objects
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00480970" target="_blank" >RIV/67985556:_____/17:00480970 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/17:00317306
Result on the web
<a href="http://dx.doi.org/10.1109/CVPR.2017.514" target="_blank" >http://dx.doi.org/10.1109/CVPR.2017.514</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2017.514" target="_blank" >10.1109/CVPR.2017.514</a>
Alternative languages
Result language
angličtina
Original language name
The World of Fast Moving Objects
Original language description
The notion of a Fast Moving Object (FMO), i.e. an object that moves over a distance exceeding its size within the exposure time, is introduced. FMOs may, and typically do, rotate with high angular speed. FMOs are very common in sports videos, but are not rare elsewhere. In a single frame, such objects are often barely visible and appear as semi-transparent streaks. A method for the detection and tracking of FMOs is proposed. The method consists of three distinct algorithms, which form an efficient localization pipeline that operates successfully in a broad range of conditions. We show that it is possible to recover the appearance of the object and its axis of rotation, despite its blurred appearance. The proposed method is evaluated on a new annotated dataset. The results show that existing trackers are inadequate for the problem of FMO localization and a new approach is required. Two applications of localization, temporal superresolution and highlighting, are presented.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ISBN
978-1-5386-0457-1
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
5203-5211
Publisher name
IEEE
Place of publication
Pisacataway
Event location
Honolulu
Event date
Jul 21, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000418371404098