Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - The influence of multi-sensor video fusion on object tracking using a particle filter
AU - Mihaylova, L.
AU - Loza, A.
AU - Nikolov, S. G.
AU - Lewis, J. J.
AU - Canga, E.-F.
AU - Li, J.
AU - Dixon, T.
AU - Canagarajah, C. N.
AU - Bull, D. R.
PY - 2006/10/2
Y1 - 2006/10/2
N2 - This paper investigates how the object tracking performance is affected by the fusion quality of videos from visible (VIZ) and infrared (IR) surveillance cameras, as compared to tracking in single modality videos. The videos have been fused using the simple averaging, and various multiresolution techniques. Tracking has been accomplished by means of a particle filter using colour and edge cues. The highest tracking accuracy has been obtained in IR sequences, whereas the VIZ video was affected by many artifacts and showed the worst tracking performance. Among the fused videos, the complex wavelet and the averaging techniques, offered the best tracking performance, comparable to that of IR. Thus, of all the methods investigated, the fused videos, containing complementary contextual information from both single modality input videos, are the best source for further analysis by a human observer or a computer program.
AB - This paper investigates how the object tracking performance is affected by the fusion quality of videos from visible (VIZ) and infrared (IR) surveillance cameras, as compared to tracking in single modality videos. The videos have been fused using the simple averaging, and various multiresolution techniques. Tracking has been accomplished by means of a particle filter using colour and edge cues. The highest tracking accuracy has been obtained in IR sequences, whereas the VIZ video was affected by many artifacts and showed the worst tracking performance. Among the fused videos, the complex wavelet and the averaging techniques, offered the best tracking performance, comparable to that of IR. Thus, of all the methods investigated, the fused videos, containing complementary contextual information from both single modality input videos, are the best source for further analysis by a human observer or a computer program.
KW - image fusion
KW - object tracking
KW - particle filtering
KW - infrared cameras
KW - visible cameras
KW - video data
KW - surveillance
M3 - Conference contribution/Paper
SN - 978-3-88579-187-4
SP - 354
EP - 358
BT - Informatik für Menschen
A2 - Hochberger, Christian
PB - Gesellschaft für Informatik
CY - Bonn
T2 - LNCS from the 2nd Workshop on Multiple Sensor Data Fusion: Solutions, Applications
Y2 - 2 October 2006 through 6 October 2006
ER -