Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Simon Hawe"'
Publikováno v:
International Journal of Computer Vision. 114:233-247
The success of many computer vision tasks lies in the ability to exploit the interdependency between different image modalities such as intensity and depth. Fusing corresponding information can be achieved on several levels, and one promising approac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2595149bb283609d46866295ef523e68
https://doi.org/10.1007/s11263-014-0786-5
https://doi.org/10.1007/s11263-014-0786-5
Publikováno v:
Computer Vision – ECCV 2014 ISBN: 9783319105987
ECCV (6)
ECCV (6)
We propose an algorithm for segmenting natural images based on texture and color information, which leverages the co-sparse analysis model for image segmentation. As a key ingredient of this method, we introduce a novel textural similarity measure, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5bb1b375c2874cba6f38043491d50835
https://doi.org/10.1007/978-3-319-10599-4_19
https://doi.org/10.1007/978-3-319-10599-4_19
Publikováno v:
CVPR
Many techniques in computer vision, machine learning, and statistics rely on the fact that a signal of interest admits a sparse representation over some dictionary. Dictionaries are either available analytically, or can be learned from a suitable tra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4131dee9bc5bb6f72e82ce90a4f27c7
https://doi.org/10.1109/cvpr.2013.63
https://doi.org/10.1109/cvpr.2013.63
In this work we address the problem of blindly reconstructing compressively sensed signals by exploiting the co-sparse analysis model. In the analysis model it is assumed that a signal multiplied by an analysis operator results in a sparse vector. We
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0f515b6903e22f44911358d88353ccc
http://arxiv.org/abs/1302.1094
http://arxiv.org/abs/1302.1094
Publikováno v:
ICCV
High-resolution depth maps can be inferred from low-resolution depth measurements and an additional high-resolution intensity image of the same scene. To that end, we introduce a bimodal co-sparse analysis model, which is able to capture the interdep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11ceb39950e21156bfdf4099c8966fb3
Autor:
Martin Kleinsteuber, Simon Hawe
Publikováno v:
Springer Proceedings in Mathematics & Statistics ISBN: 9781461450757
The reconstruction of a signal from only a few measurements, deconvolving, or denoising are only a few interesting signal processing applications that can be formulated as linear inverse problems. Commonly, one overcomes the ill-posedness of such pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de20066b74ceb668a2e9dd5a2f1ad173
https://doi.org/10.1007/978-1-4614-5076-4_7
https://doi.org/10.1007/978-1-4614-5076-4_7
Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes that images can be decomposed into a linear combination of very few atom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de87033264c682fb7be8a31c6acb2b2b
http://arxiv.org/abs/1204.5309
http://arxiv.org/abs/1204.5309
Publikováno v:
ICASSP
This paper considers the problem of reconstructing images from only a few measurements. A method is proposed that is based on the theory of Compressive Sensing. We introduce a new prior that combines an l p -pseudo-norm approximation of the image gra
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::95565c10aa9463ded76d4aa6665b5e74
https://doi.org/10.1109/icassp.2012.6287984
https://doi.org/10.1109/icassp.2012.6287984
Swarm Intelligence uses a set of agents which are able to move and gather local information in a search space and utilize communication, limited memory, and intelligence for problem solving. In this work, we present an agent-based algorithm which is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05934c02272020c90eab99fa692d02ae
https://mediatum.ub.tum.de/1127764
https://mediatum.ub.tum.de/1127764
Publikováno v:
ICCV
In this work we propose a method for estimating disparity maps from very few measurements. Based on the theory of Compressive Sensing, our algorithm accurately reconstructs disparity maps only using about 5% of the entire map. We propose a conjugate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dfbd72d157636470342da8b270ca9b60
https://doi.org/10.1109/iccv.2011.6126488
https://doi.org/10.1109/iccv.2011.6126488