Multiple Object Tracking using K-Shortest Paths Optimization
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We present an integrated schedule planning model where the decisions of schedule design, fleeting and pricing are made simultaneously. Pricing is integrated through a logit demand model where itinerary choice is modeled by defining the utilities of the alt ...
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Multi-object tracking can be achieved by detecting objects in individual frames and then linking detections across frames. Such an approach can be made very robust to the occasional detection failure: If an object is not detected in a frame but is in previ ...
This thesis deals with models and methods for large scale optimization problems; in particular, we focus on decision problems arising in the context of seaport container terminals for the efficient management of terminal operations. Large-scale optimizatio ...
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Video surveillance is currently undergoing a rapid growth. However, while thousands of cameras are being installed in public places all over the world, computer programs that could reliably detect and track people in order to analyze their behavior are not ...
We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solutio ...
We propose a new heuristic for nonlinear global optimization combining a variable neighborhood search framework with a modified trust-region algorithm as local search. The proposed method presents the capability to prematurely interrupt the local search if ...