Title :
The Effect of Pixel-Level Fusion on Object Tracking in Multi-Sensor Surveillance Video
Author :
Cvejic, N. ; Nikolov, S.G. ; Knowles, H.D. ; Loza, A. ; Achim, A. ; Bull, D.R. ; Canagarajah, C.N.
Author_Institution :
Univ. of Bristol, Bristol
Abstract :
This paper investigates the impact of pixel-level fusion of videos from visible (VIZ) and infrared (IR) surveillance cameras on object tracking performance, as compared to tracking in single modality videos. Tracking has been accomplished by means of a particle filter which fuses a colour cue and the structural similarity measure (SSIM). The highest tracking accuracy has been obtained in IR sequences, whereas the VIZ video showed the worst tracking performance due to higher levels of clutter. However, metrics for fusion assessment clearly point towards the supremacy of the multiresolutional methods, especially Dual Tree-Complex Wavelet Transform method. Thus, a new, tracking-oriented metric is needed that is able to accurately assess how fusion affects the performance of the tracker.
Keywords :
image resolution; image sequences; particle filtering (numerical methods); sensor fusion; video surveillance; wavelet transforms; IR sequences; dual tree-complex wavelet transform method; fusion assessment; infrared surveillance cameras; multisensor surveillance video; object tracking; particle filter; pixel-level fusion; single modality videos; structural similarity measure; tracking-oriented metric; visible surveillance cameras; Cameras; Filtering; Fuses; Histograms; Humans; Infrared surveillance; Optical fiber communication; Particle tracking; Target tracking; Video sequences;
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2007.383433
