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Seibert H.,Fraunhofer Institute for Computer Graphics Research
Proceedings of the 2012 8th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2012 | Year: 2012

The segmentation of the face in 3D reconstructions is a crucial processing step within 3D face recognition systems. At this early processing stage discarding other surface portions such as collars, hats or hairstyle shall reduce the amount of data. In contrast to other approaches, the proposed algorithm uses only the face geometry and is therefore robust with respect to lighting conditions or texture quality. Assuming the skin region of a face is locally flat and closed, a binary mask image is created. Morphology and a simple heuristic are applied on connected components to select and join appropriate components. The implementation is straight forward, yielding just a few parameters and copes the problem without training procedure. A proof of concept is given and results are shown for several cases, limitations of the approach are discussed. © 2012 IEEE. Source


Le Moan S.,TU Darmstadt | Urban P.,Fraunhofer Institute for Computer Graphics Research
IEEE Transactions on Image Processing | Year: 2014

We propose a new strategy to evaluate the quality of multi and hyperspectral images, from the perspective of human perception. We define the spectral image difference as the overall perceived difference between two spectral images under a set of specified viewing conditions (illuminants). First, we analyze the stability of seven image-difference features across illuminants, by means of an information-theoretic strategy. We demonstrate, in particular, that in the case of common spectral distortions (spectral gamut mapping, spectral compression, spectral reconstruction), chromatic features vary much more than achromatic ones despite considering chromatic adaptation. Then, we propose two computationally efficient spectral image difference metrics and compare them to the results of a subjective visual experiment. A significant improvement is shown over existing metrics such as the widely used root-mean square error. © 2014 IEEE. Source


Preiss J.,TU Darmstadt | Fernandes F.,TU Darmstadt | Urban P.,Fraunhofer Institute for Computer Graphics Research
IEEE Transactions on Image Processing | Year: 2014

While image-difference metrics show good prediction performance on visual data, they often yield artifact-contaminated results if used as objective functions for optimizing complex image-processing tasks. We investigate in this regard the recently proposed color-image-difference (CID) metric particularly developed for predicting gamut-mapping distortions. We present an algorithm for optimizing gamut mapping employing the CID metric as the objective function. Resulting images contain various visual artifacts, which are addressed by multiple modifications yielding the improved color-image-difference (iCID) metric. The iCID-based optimizations are free from artifacts and retain contrast, structure, and color of the original image to a great extent. Furthermore, the prediction performance on visual data is improved by the modifications. © 2013 IEEE. Source


Steger S.,Fraunhofer Institute for Computer Graphics Research
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention | Year: 2012

This paper presents a novel skeleton based method for the registration of head&neck datasets. Unlike existing approaches it is fully automated, spatial relation of the bones is considered during their registration and only one of the images must be a CT scan. An articulated atlas is used to jointly obtain a segmentation of the skull, the mandible and the vertebrae C1-Th2 from the CT image. These bones are then successively rigidly registered with the moving image, beginning at the skull, resulting in a rigid transformation for each of the bones. Linear combinations of those transformations describe the deformation in the soft tissue. The weights for the transformations are given by the solution of the Laplace equation. Optionally, the skin surface can be incorporated. The approach is evaluated on 20 CT/MRI pairs of head&neck datasets acquired in clinical routine. Visual inspection shows that the segmentation of the bones was successful in all cases and their successive alignment was successful in 19 cases. Based on manual segmentations of lymph nodes in both modalities, the registration accuracy in the soft tissue was assessed. The mean target registration error of the lymph node centroids was 5.33 +/- 2.44 mm when the registration was solely based on the deformation of the skeleton and 5.00 +/- 2.38 mm when the skin surface was additionally considered. The method's capture range is sufficient to cope with strongly deformed images and it can be modified to support other parts of the body. The overall registration process typically takes less than 2 minutes. Source


Happel K.,TU Darmstadt | Dorsam E.,TU Darmstadt | Urban P.,Fraunhofer Institute for Computer Graphics Research
Optics Express | Year: 2014

Subsurface light transport can affect the visual appearance of materials significantly. Measuring and modeling this phenomenon is crucial for accurately reproducing colors in printing or for rendering translucent objects on displays. In this paper, we propose an apparatus to measure subsurface light transport employing a reference material to cancel out adverse signals that may bias the results. In contrast to other approaches, the setup enables improved focusing on rough surfaces (e.g. uncoated paper). We derive a measurement equation that may be used to deduce the point spread function (PSF) of subsurface light transport. Main contributions are the usage of spectrally-narrowband exchangeable LEDs allowing spectrally-resolved measurements and an approach based on quadratic programming for reconstructing PSFs in the case of isotropic light transport. © 2014 Optical Society of America. Source

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