bibtype |
J -
Journal Article
|
ARLID |
0345450 |
utime |
20240103193650.7 |
mtime |
20110816235959.9 |
WOS |
000293961900002 |
SCOPUS |
80053895602 |
DOI |
10.1007/s00138-010-0251-6 |
title
(primary) (eng) |
Dynamic texture as foreground and background |
specification |
|
serial |
ARLID |
cav_un_epca*0254218 |
ISSN |
0932-8092 |
title
|
Machine Vision and Applications |
volume_id |
22 |
volume |
5 (2011) |
page_num |
741-750 |
publisher |
|
|
keyword |
Dynamic texture |
keyword |
Optical flow |
keyword |
SVD |
author
(primary) |
ARLID |
cav_un_auth*0216372 |
name1 |
Chetverikov |
name2 |
D. |
country |
HU |
|
author
|
ARLID |
cav_un_auth*0273706 |
name1 |
Fazekas |
name2 |
S. |
country |
HU |
|
author
|
ARLID |
cav_un_auth*0101093 |
name1 |
Haindl |
name2 |
Michal |
full_dept (cz) |
Rozpoznávání obrazu |
full_dept |
Department of Pattern Recognition |
department (cz) |
RO |
department |
RO |
institution |
UTIA-B |
full_dept |
Department of Pattern Recognition |
fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
source |
|
cas_special |
project |
project_id |
GA102/08/0593 |
agency |
GA ČR |
ARLID |
cav_un_auth*0239567 |
|
project |
project_id |
507752 |
country |
XE |
agency |
EC |
ARLID |
cav_un_auth*0200689 |
|
research |
CEZ:AV0Z10750506 |
abstract
(eng) |
Depending on application, temporal texture can be viewed as either foreground or background. We address two related problems: finding regions of dynamic texture in a video and detecting moving targets in a dynamic texture. We propose efficient and fast methods for both cases. The methods can be potentially used in real-time applications of machine vision. First, we show how the optical flow residual can be used to find dynamic texture in video. The algorithm is a practical, real-time simplification of the sophisticated and powerful but time-consuming method (Fazekas et al. in Int J Comput Vis 82:48–63, 2009). We give numerous examples of detecting and segmenting fire, smoke, water and other dynamic textures in real-world videos acquired by static and moving cameras. Then we apply the singular value decomposition (SVD) to a temporal data window in a video to detect targets in dynamic texture via the residual of the largest singular value. |
reportyear |
2012 |
RIV |
BD |
mrcbC52 |
4 A 4a 20231122134102.9 |
permalink |
http://hdl.handle.net/11104/0186722 |
mrcbT16-e |
COMPUTERSCIENCEARTIFICIALINTELLIGENCE|COMPUTERSCIENCECYBERNETICS|ENGINEERINGELECTRICALELECTRONIC |
mrcbT16-f |
1.324 |
mrcbT16-g |
0.132 |
mrcbT16-h |
7.6 |
mrcbT16-i |
0.00254 |
mrcbT16-j |
0.669 |
mrcbT16-k |
711 |
mrcbT16-l |
76 |
mrcbT16-s |
0.501 |
mrcbT16-4 |
Q1 |
mrcbT16-B |
60.988 |
mrcbT16-C |
44.225 |
mrcbT16-D |
Q2 |
mrcbT16-E |
Q3 |
arlyear |
2011 |
mrcbTft |
\nSoubory v repozitáři: haindl-0345450.pdf |
mrcbU14 |
80053895602 SCOPUS |
mrcbU34 |
000293961900002 WOS |
mrcbU63 |
cav_un_epca*0254218 Machine Vision and Applications 0932-8092 1432-1769 Roč. 22 č. 5 2011 741 750 Springer |
|