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We present a system that allows for changing the major camera parameters after the acquisition of an image. Using the high dynamic range composition technique and additional range information captured with a small and low-cost time-of-flight camera, our setup enables us to set the main parameters of a virtual camera system and to compute the resulting image. Hence, the aperture size and shape, exposure...
We present a framework that allows for localization based on very low resolution omnidirectional image data using regression techniques. Previous related methods are constrained to image data labeled with exact position information acquired in the training phase. We relax this constraint and propose to learn local heteroscedastic Gaussian processes by accumulating odometry data which can easily be...
We present a framework that allows for localization based on very low resolution omnidirectional image data using regression techniques. Previous related methods are constrained to image data labeled with exact position information acquired in the training phase. We relax this constraint and propose to learn local heteroscedastic Gaussian processes by accumulating odometry data which can easily be...
We present an algorithm that finds the rotation which best aligns a given configuration of directions on an unsorted set of directions. Using a cost function that we derive in the paper, we show that this algorithm efficiently finds the optimal coordinate frame for a given 3D data set in order to maximize the performance of axis-aligned bounding volumes such as octrees or occupancy grids with regard...
We address the problem of registering a set of 2D laser scans in 3D space with regard to six degrees of freedom. Registering single 2D scans is only possible when making strong assumptions on the structure of the scene or on the acquisition process, since only a slice of the 3D environment is captured and the information content is very limited. With a combination of two differently oriented laser...
We present an integrated method for post-processing of range data which removes outliers, smoothes the depth values and enhances the lateral resolution in order to achieve visually pleasing 3D models from low-cost depth sensors with additional (registered) color images. The algorithm is based on the non-local principle and adapts the original NL-Means formulation to the characteristics of typical...
Orientation estimation based on image data is a key technique in many applications. Robust estimates are possible in case of omnidirectional images due to the large field of view of the camera. Traditionally, techniques based on local image features have been applied to this kind of problem. Another very efficient technique is to formulate the problem in terms of correlation on the sphere and to solve...
We investigate the application of particle filters to estimate the orientation of a mobile agent based on an omnidirectional video stream. By applying spherical signal analysis to sequences of low resolution input images we perform a real-time estimation of the relative camera rotation. We use normalized cross-correlation computed with a fast frequency domain approach that yields unbiased estimates...
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