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ECCV
2008
Springer
14 years 9 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
BMCBI
2008
220views more  BMCBI 2008»
13 years 7 months ago
Gene prediction in metagenomic fragments: A large scale machine learning approach
Background: Metagenomics is an approach to the characterization of microbial genomes via the direct isolation of genomic sequences from the environment without prior cultivation. ...
Katharina J. Hoff, Maike Tech, Thomas Lingner, Rol...
ICPR
2010
IEEE
13 years 10 months ago
Natural Material Recognition with Illumination Invariant Textural Features
Abstract—A visual appearance of natural materials fundamentally depends on illumination conditions, which significantly complicates a real scene analysis. We propose textural fe...
Pavel Vacha, Michael Haindl
SMI
2010
IEEE
188views Image Analysis» more  SMI 2010»
13 years 5 months ago
Sharp Feature Detection in Point Clouds
—This paper presents a new technique for detecting sharp features on point-sampled geometry. Sharp features of different nature and possessing angles varying from obtuse to acute...
Christopher Weber, Stefanie Hahmann, Hans Hagen
CVPR
2009
IEEE
15 years 1 months ago
Tracking of Cell Populations to Understand their Spatio-Temporal Behavior in Response to Physical Stimuli
We have developed methods for segmentation and tracking of cells in time-lapse phase-contrast microscopy images. Our multi-object Bayesian algorithm detects and tracks large num...
David House, Matthew Walker, Zheng Wu, Joyce Wong,...