TY  - JOUR
AU  - Ferran Diego
AU  - Daniel Ponsa
AU  - Joan Serrat
AU  - Antonio Lopez
PY  - 2011//
TI  - Video Alignment for Change Detection
T2  - TIP
JO  - IEEE Transactions on Image Processing
SP  - 1858
EP  - 1869
VL  - 20
IS  - 7
KW  - video alignment
N2  - In this work, we address the problem of aligning two video sequences. Such alignment refers to synchronization, i.e., the establishment of temporal correspondence between frames of the first and second video, followed by spatial registration of all the temporally corresponding frames. Video synchronization and alignment have been attempted before, but most often in the relatively simple cases of fixed or rigidly attached cameras and simultaneous acquisition. In addition, restrictive assumptions have been applied, including linear time correspondence or the knowledge of the complete trajectories of corresponding scene points; to some extent, these assumptions limit the practical applicability of any solutions developed. We intend to solve the more general problem of aligning video sequences recorded by independently moving cameras that follow similar trajectories, based only on the fusion of image intensity and GPS information. The novelty of our approach is to pose the synchronization as a MAP inference problem on a Bayesian network including the observations from these two sensor types, which have been proved complementary. Alignment results are presented in the context of videos recorded from vehicles driving along the same track at different times, for different road types. In addition, we explore two applications of the proposed video alignment method, both based on change detection between aligned videos. One is the detection of vehicles, which could be of use in ADAS. The other is online difference spotting videos of surveillance rounds.
L1  - http://refbase.cvc.uab.es/files/dps2011.pdf
N1  - ADAS; IF
ID  - Ferran Diego2011
ER  -