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- 2014 (3) (remove)
3D-models are getting more important in many areas such as multimedia applications, robotics or film industries. Of particular interest is the creation of 3D-models from a series of monocular images. This is because the cameras that are required for this purpose are becoming cheaper, smaller and more sophisticated at the same time. Increasingly often, suitable cameras are already integrated in devices like smartphones, tablet PCs or cars for example. Hence, there is a great potential for applications of this reconstruction technique.
This thesis is based on the use of a series of images that were taken with arncalibrated camera. The first step is to extract point correspondences from this image series making use of the well-known SURF- and A-KAZE-features. Starting from the point correspondences, it is possible to reconstruct a 3D-Modell with different algorithms that consists of a point cloud and camera poses. To reduce errors in the 3D-model, this thesis especially focuses on explaining the bundle adjustment algorithm, which is being used for a non-linear error minimization of a cost function.
The thesis also introduces the application for the 3D-reconstruction and the visualization of the results, that was developed in the course of this thesis.
The implemented system is evaluated based on statistics and the newly aquiredrnknowledge is presented. The thesis concludes with a summary of its results, and a number of ideas for potential future applications and developments.
Online Handschrifterkennung chinesischer Schriftzeichen auf androidfähigen mobilen Endgeräten
(2014)
Usage of mobile dictionaries or translators requires an input. This input has to be processed and recognized beforehand. Chinese characters are more suited for a handwritten input than a keyboard based one. Reason for that are the characters consisting mostly of pictograms or ideograms.
This thesis deals with an implementation of a prototypical recognition system on a mobile device. The recognition process should be online and therefore running while writing. It can save time for the user, because suggestions are made during runtime.
Basics and an overview over the current state of the art in online handwriting recognition will be given. An approach will be chosen and implemented, such that the recognition process is fast and needs little memory. The implementation will be tested and it will show, that a fast recognition can be possible on small devices. Suggestions for expansions and improvements will be given, including a future work part.
The goal of this work is evaluation and optimization of several eye-tracking algorithms for estimation of relevant features regarding accuracy. The extracted features are pupil- and glintcenters. The algorithms are applicable to off the shelf cameras. A synthetic model of the eye was modified and utilized. The model was used to supply ground truth for the evaluation of the methods.