Tracking of moving objects using mathematical imaging

Zwienenberg, Jesse (2017) Tracking of moving objects using mathematical imaging.

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Abstract:Estimating the motion of objects in image sequences is a problem which arises in several research areas like image processing, bio-medical imaging and machine vision. The motion induced on the image plane by the objects is called the optical flow and in this work we compute this using two vastly different methods. Firstly we look at variational models which use the image derivatives in the setting of convex energy functional minimization to compute the optical flow between images. The second method that we discuss is known as deep learning and revolves around the usage of convolutional neural networks. To compare the performance of both methods we implemented the variational models from scratch and for the deep learning approach we use a publicly available pre-trained model.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics
Programme:Applied Mathematics BSc (56965)
Link to this item:http://purl.utwente.nl/essays/73120
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