JavaScript is disabled for your browser. Some features of this site may not work without it.
Please be advised that the site will be down for maintenance on Sunday, September 1, 2024, from 08:00 to 18:00, and again on Monday, September 2, 2024, from 08:00 to 09:00. We apologize for any inconvenience this may cause.
A comparative study of multiple hypothesis and Viterbi based track stitching
The track stitching problem can be divided into two tasks, namely target tracking to create track fragments,
and track stitching to stitch the resulting track fragments together. In this study a tracking
algorithm is developed to track multiple targets and to create track fragments. The track fragments
are generated through the use of a Markov model where a target can be assumed to be in an occluded
or a visible state. The track fragments are modelled as nodes in a state diagram, which in turn is
used to create a time dependent trellis diagram. The columns in the trellis diagram represents the
time when a particular track fragment appeared while the nodes represent certain kinematic features
of the track fragments themselves. This trellis is then solved using a sequential Viterbi algorithm and
using each node exactly once, to obtain the most viable track fragment to track fragment associations.
Each solution path through the trellis diagram represents a set of track fragments which where created
by a specific target. Results are presented by simulating multiple crossing targets with fragmented
tracks. It is shown that the algorithm successfully stitches track fragments together in the presence of
false tracks caused by noisy observations. Further evaluation of the performance of the algorithm is
presented with a number of scenarios where increasingly ambiguous track fragment to track fragment
associations exist. The sequential Viterbi track stitching algorithm is also compared against a multiple
hypothesis track fragment stitching algorithm. This algorithm was extended from the classic hypothesis
based multiple hypothesis tracking algorithm (MHT) by, performing track fragment to track
associations instead of observation to track associations. In these comparisons, the code used to run
the simulations have been optimised and vectorised as far as possible to ensure a fair comparison. It
is shown that the Viterbi based track stitching algorithm performs somewhat better that the multiple
hypothesis track stitching algorithm for similar execution times. The Viterbi based track stitching
algorithm is also shown to produce more consistently acceptable results.
Die volgersegmentsamevoegingprobleem kan verdeel word in twee hooftake, naamlik teikenvolging,
waar die volgersegmente geskep word en volgersegmentstikking, waar die geskepte segmente met
mekaar geassosieer word. In hierdie studie word ?n volgeraloritme ontwikkel om veelvuldige teikens
te volg en om volgersegmente te skep. Die volgersegmente word geskep deur gebruik te maak van
?n Markov-model waar ?n teiken in ?n versteekte of ?n sigbare toestand kan wees. Die volgersegmente
word gemodelleer as nodes in ?n toestandsdiagram, wat omgeskakel word in ?n tyd-afhanklike
latwerkdiagram. Die kolomme in hierdie diagram stel die tyd voor wanneer ?n spesifieke volgersegment
sigbaar geword het, terwyl die nodes die volgersegmente voorstel. Hierdie latwerk diagram
word dan opgelos deur gebruik te maak van ?n sekwensi?le Viterbi-algoritme waar elke node slegs
een keer in die oplossing gebruik word om die mees waarskynlike paaie te verkry. Elke pad deur
die diagram stel ?n groep volgersegmente voor wat deur ?n spesifieke teiken gegenereer is. Resultate
word voorgel? deur veelvuldige kruisende teikens te genereer waarvan die teikenwaarnemings
yl is. Daar word aangetoon dat die algoritme die volgersegmente korrek met mekaar assosieer in
die teenwoordigheid van vals volgersegmente wat deur valsalarmwaarnemings veroorsaak is. Verdere
evaluering, volgens die prestasie van die algoritme, word aangetoon deur ?n aantal gevalle te
simuleer waar die assosiasies tussen die volger segmente meer dubbelsinning is. Die opeenvolgende
Viterbi-volgersegmentstikkingalgorithme word laastens vergelyk met ?n veelvuldige-hipotese volgersegmentstikkingalgorithme
wat uitgebrei is uit die hipotese-gebaseerde veelvuldige-hipotese volgeralgoritme
om segment met segment te assosieer in plaas daarvan om waarnemings met volgers te
assosieer. In hierdie vergelykings is die kode gebruik is om die simulasies uit te voer so ver moontlik
geoptimeer om sodoende ?n eerlike vergelyking te kan tref. Die Viterbi-gebaseerde algoritme vaar
ietwat beter as die veelvuldige-hipotese algoritme in gevalle waar die uitvoertye soortgelyk is. Die
Viterbi-gebaseerde algoritme blyk ook meer konsekwent te wees, en lewer dus meer aanvaarbare
resultate.
Description:
Dissertation (MEng)--University of Pretoria, 2016.