@conference {andres_08_segmentation,
	title = {Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification},
	booktitle = {Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings},
	volume = {5096},
	year = {2008},
	note = {1},
	pages = {142-152},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-69321-5_15},
	author = {Bj{\"o}rn Andres and Ullrich K{\"o}the and Helmstaedter, M. and Denk, W. and Fred A. Hamprecht},
	editor = {Gerhard Rigoll}
}
@conference {andres_07_selection,
	title = {Selection of Local Optical Flow Models by Means of Residual Analysis},
	booktitle = {Pattern Recognition},
	volume = {4713},
	year = {2007},
	note = {1},
	pages = {72-81},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-74936-3_8},
	author = {Bj{\"o}rn Andres and Fred A. Hamprecht and Christoph S. Garbe},
	editor = {Christoph Schn{\"o}rr and Bernd J{\"a}hne and Fred A. Hamprecht}
}
@conference {andres2007,
	title = {Selection of local optical flow models by means of residual analysis},
	booktitle = {Proceedings of the 29th DAGM Symposium on Pattern Recognition},
	year = {2007},
	pages = {72--81},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This contribution presents a novel approach to the challenging problem of model selection in motion estimation from sequences of images. New light is cast on parametric models of local optical flow. These models give rise to parameter estimation problems with highly correlated errors in variables (EIV). Regression is hence performed by equilibrated total least squares. The authors suggest to adaptively select motion models by testing local empirical regression residuals to be in accordance with the probability distribution that is theoretically predicted by the EIV model. Motion estimation with residual-based model selection is examined on artificial sequences designed to test specifically for the properties of the model selection process. These simulations indicate a good performance in the exclusion of inappropriate models and yield promising results in model complexity control.},
	doi = {10.1007/978-3-540-74936-3_8},
	author = {Bj{\"o}rn Andres and Christoph S. Garbe and Christoph Schn{\"o}rr and Bernd J{\"a}hne},
	editor = {Fred A. Hamprecht and Fred A. Hamprecht}
}
