Matching Traffic Objects recorded by Stereoscopic Cameras
Typ
Examensarbete för masterexamen
Program
Publicerad
2020
Författare
Phung, Tommy
Areback, Stefan
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
If one uses several cameras to film different but overlapping parts of a scene (in
our case an intersection), then a way to get an overview of the scene, is to relate
all the cameras to a single coordinate system. This can be done manually using
knowledge of the positions relative to the different cameras of objects that show up
in the overlapping part of the filmed scene. However, it would be preferable (to save
time, amongst other things) if this process could be automated, using information
recorded by the cameras (in this case the positions, velocities and timestamps of
traffic objects filmed by the camera). The suggested methods for achieving this is
Coherent point drift (CPD) with the use of Expectation maximization (EM).
Once a common coordinate system has been found, one still needs to merge the
trajectories from the different cameras corresponding to the same traffic object into
a single trajectory. Preferably, this too should be done using only the information
recorded by the camera (positions, velocities, timestamps). For finding a merge, the
presented method is a modified version of Longest Common Subsequence (LCSS)
with respect to the camera views and their overlap, presented as polygons.
CPD performs well for two cameras when LCSS is being applied as a method
for noise reduction whereas when there are three cameras it gives an ambivalent
solution. Using LCSS when matching trajectories for merging performs well for
both two and three cameras, however the merging methods needs some additional
calibrations.
Beskrivning
Ämne/nyckelord
Point set registration , Coherent point drift , Expectation maximization , Longest Common Subsequence , camera alignment