André Gooßen

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The complexity in face recognition emerges from the variability of the appearance of a human face. While the identity is preserved, the appearance of a face may change due to factors such as illumination, pose or facial expression. To recognize a person independent of pose, we want to separate shape from texture information. We concentrate on the texture(More)
In this paper we propose an extension of active shape model based bone segmentation. We examine the benefit of using multiple candidates for new landmark positions during segmentation. To incorporate this information we compare three strategies of adapting the fitting algorithm. For evaluation we segmented the hip, knee and ankle joints in more than 100(More)
We present an algorithm for fast automatic registration of spatially overlapping radiographs. It possesses strong robustness against noise, feature masking and feature displacement. Pivotal for this algorithm is an actual interpretation of the stitching feature instead of a simple detection. The proposed method has been evaluated on 3000 clinical(More)
title = {Facial pose estimation using active appearance models and a generic face model}, booktitle = {Proceedings of VISAPP 2010-International Conference on Computer Vision Theory and Applications}, publisher = {INSTICC}, year = {2010}, pages = {499-506} } Abstract: The complexity in face recognition emerges from the variability of the appearance of human(More)
In this paper we propose a method to enhance Active Shape Model based bone segmentation. One major weakness of the classic algorithm is the use of a single dedicated image feature. However to model the variation of image content along the object boundaries it is more suitable to use different features for different regions. We derive an automatic(More)