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Institute
- Institut für Computervisualistik (282) (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.
Today, augmented reality is becoming more and more important in several areas like industrial sectors, medicine, or tourism. This gain of importance can easily be explained by its powerful extension of real world content. Therefore, augmented realty became a way to explain and enhance the real world information. Yet, to create a system which can enhance a scene with additional information, the relation between the system and the real world must be known. In order to establish this relationship a commonly used method is optical tracking. The system calculates its relation to the real world from camera images. To do so, a reference which is known is needed in the scene to serve as an orientation. Today, this is mostly a 2D-marker or a 2D-texture. These are placed in the real world scenery to serve as a reference. But, this is an intrusion in the scene. That is why it is desirable that the system works without such an additional aid. An strategy without manipulating the scene is object-tracking. In this approach, any object from the scene can be used as a reference for the system. As an object is far more complex than a marker, it is harder for the system to establish its relationship with the real world. That is why most methods for 3D-object-tracking reduce the object by not using the whole object as reference. The focus of this thesis is to research how a whole object can be used as a reference in a way that either the system or the camera can be moved in any 360 degree angle around the object without loosing the relation to the real world. As a basis the augmented reality framework, the so called VisionLib, is used. Extensions to this system for 360 degree tracking are implemented in different ways and analyzed in the scope of this work. Also, the different extensions are compared. The best results were achieved by improving the reinitialization process. With this extension, current camera images of the scene are given to the system. With the hek of these images, the system can calculate the relation to the real world faster in case the relation went missing.