| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0480970 |
| utime |
20240111140949.6 |
| mtime |
20171107235959.9 |
| SCOPUS |
85038564492 |
| WOS |
000418371404098 |
| DOI |
10.1109/CVPR.2017.514 |
| title
(primary) (eng) |
The World of Fast Moving Objects |
| specification |
| page_count |
9 s. |
| media_type |
E |
|
| serial |
| ARLID |
cav_un_epca*0480969 |
| ISBN |
978-1-5386-0457-1 |
| title
|
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
| page_num |
5203-5211 |
| publisher |
| place |
Pisacataway |
| name |
IEEE |
| year |
2017 |
|
|
| keyword |
tracking |
| keyword |
blind deconvolution |
| keyword |
deblurring |
| keyword |
temporal superresolution |
| author
(primary) |
| ARLID |
cav_un_auth*0352947 |
| name1 |
Rozumnyi |
| name2 |
D. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0293863 |
| name1 |
Kotera |
| name2 |
Jan |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| country |
CZ |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101209 |
| name1 |
Šroubek |
| name2 |
Filip |
| institution |
UTIA-B |
| full_dept (cz) |
Zpracování obrazové informace |
| full_dept |
Department of Image Processing |
| department (cz) |
ZOI |
| department |
ZOI |
| full_dept |
Department of Image Processing |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0209819 |
| name1 |
Novotný |
| name2 |
L. |
| country |
CZ |
|
| author
|
| ARLID |
cav_un_auth*0075799 |
| name1 |
Matas |
| name2 |
J. |
| country |
CZ |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0338628 |
| project_id |
GA16-13830S |
| agency |
GA ČR |
| country |
CZ |
|
| abstract
(eng) |
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. |
| action |
| ARLID |
cav_un_auth*0352949 |
| name |
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
| dates |
20170721 |
| mrcbC20-s |
20170726 |
| place |
Honolulu |
| country |
US |
|
| RIV |
JD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20205 |
| reportyear |
2018 |
| num_of_auth |
5 |
| mrcbC52 |
4 A hod 4ah 20231122142802.5 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0276746 |
| cooperation |
| ARLID |
cav_un_auth*0331345 |
| name |
FEL Czech Technical University |
| institution |
FET CTU |
| country |
CZ |
|
| mrcbC64 |
1 Department of Image Processing UTIA-B 10200 COMPUTER SCIENCE, THEORY & METHODS |
| confidential |
S |
| mrcbC86 |
n.a. Proceedings Paper Computer Science Artificial Intelligence|Computer Science Theory Methods|Engineering Electrical Electronic |
| arlyear |
2017 |
| mrcbTft |
\nSoubory v repozitáři: sroubek-0480970.pdf |
| mrcbU14 |
85038564492 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000418371404098 WOS |
| mrcbU56 |
pdf 5.2MB |
| mrcbU63 |
cav_un_epca*0480969 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 978-1-5386-0457-1 5203 5211 Pisacataway IEEE 2017 |
|