By David Van Hamme, Peter Veelaert, Wilfried Philips (auth.), Jacques Blanc-Talon, Richard Kleihorst, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)
This e-book constitutes the refereed court cases of the thirteenth foreign convention on complex innovations for clever imaginative and prescient structures, ACIVS 2011, held in Ghent, Belgium, in August 2011.
The sixty six revised complete papers offered have been rigorously reviewed and chosen from 124 submissions. The papers are geared up in topical sections on type popularity, and monitoring, segmentation, photos research, photo processing, video surveillance and biometrics, algorithms and optimization; and 3D, intensity and scene understanding.
Read Online or Download Advanced Concepts for Intelligent Vision Systems: 13th International Conference, ACIVS 2011, Ghent, Belgium, August 22-25, 2011. Proceedings PDF
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Additional info for Advanced Concepts for Intelligent Vision Systems: 13th International Conference, ACIVS 2011, Ghent, Belgium, August 22-25, 2011. Proceedings
Data Mining and Knowledge Discovery, 283–304 (1998) 13. : Modeling the shape of the scene: a holistic representation of the spatial envelope. International Journal of Computer Vision 42(3), 145–175 (2001) 14. : Scene classiﬁcation using a hybrid generative/discriminative approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(4), 712–727 (2008) Nonparametric Estimation of Fisher Vectors to Aggregate Image Descriptors Herv´e Le Borgne and Pablo Mu˜noz Fuentes CEA, LIST, Laboratory of Vision and Content Engineering 18 route du Panorama, BP6, Fontenay-au-Roses, F-92265 France Abstract.
In the context of learning and recognizing objects in 3D environments diﬀerent theories exist about the brain functions. g. , are simpler for implementation in vision systems of mobile robots. The psychological model in  suggests learning of canonical views for object representations. The work presented in  shows capability of learning three dimensional structure not only by looking at the target object or environment from diﬀerent directions but by imagining to view it from these orientations as well.
Such a binary weighting scheme is commonly used in the design of BOV, in particular when the codebook is large . 6 Independent Low Level Features According to equation (11) the signature derivation requires to use independent lowlevel features, such that the image description density could be expressed as a factorial code. Such features can be obtained with Independent Component Analysis (ICA)[2,6] that is a class of methods that aims at revealing statistically independent latent variables of observed data.
Advanced Concepts for Intelligent Vision Systems: 13th International Conference, ACIVS 2011, Ghent, Belgium, August 22-25, 2011. Proceedings by David Van Hamme, Peter Veelaert, Wilfried Philips (auth.), Jacques Blanc-Talon, Richard Kleihorst, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)