caa a22 4500 467914192 CHVBK 20180406152857.0 cr unu---uuuuu 170328e20060801xx s 000 0 eng 10.1007/s11263-006-6851-y doi (NATIONALLICENCE)springer-10.1007/s11263-006-6851-y Higher Order Active Contours [Elektronische Daten] [Marie Rochery, Ian Jermyn, Josiane Zerubia] We introduce a new class of active contour models that hold great promise for region and shape modelling, and we apply a special case of these models to the extraction of road networks from satellite and aerial imagery. The new models are arbitrary polynomial functionals on the space of boundaries, and thus greatly generalize the linear functionals used in classical contour energies. While classical energies are expressed as single integrals over the contour, the new energies incorporate multiple integrals, and thus describe long-range interactions between different sets of contour points. As prior terms, they describe families of contours that share complex geometric properties, without making reference to any particular shape, and they require no pose estimation. As likelihood terms, they can describe multi-point interactions between the contour and the data. To optimize the energies, we use a level set approach. The forces derived from the new energies are non-local however, thus necessitating an extension of standard level set methods. Networks are a shape family of great importance in a number of applications, including remote sensing imagery. To model them, we make a particular choice of prior quadratic energy that describes reticulated structures, and augment it with a likelihood term that couples the data at pairs of contour points to their joint geometry. Promising experimental results are shown on real images. Springer Science + Business Media, LLC, 2006 active contour nationallicence shape prior nationallicence geometric nationallicence higher-order nationallicence polynomial nationallicence quadratic nationallicence road network nationallicence remote sensing nationallicence Rochery Marie Ariana (joint research group INRIA/I3S), INRIA, Sophia Antipolis Cedex, B.P. 93, 06902, France aut Jermyn Ian Ariana (joint research group INRIA/I3S), INRIA, Sophia Antipolis Cedex, B.P. 93, 06902, France aut Zerubia Josiane Ariana (joint research group INRIA/I3S), INRIA, Sophia Antipolis Cedex, B.P. 93, 06902, France aut International Journal of Computer Vision Kluwer Academic Publishers 69/1(2006-08-01), 27-42 0920-5691 69:1<27 2006 69 11263 https://doi.org/10.1007/s11263-006-6851-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11263-006-6851-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Rochery Marie Ariana (joint research group INRIA/I3S), INRIA, Sophia Antipolis Cedex, B.P. 93, 06902, France aut NATIONALLICENCE 700 1- Jermyn Ian Ariana (joint research group INRIA/I3S), INRIA, Sophia Antipolis Cedex, B.P. 93, 06902, France aut NATIONALLICENCE 700 1- Zerubia Josiane Ariana (joint research group INRIA/I3S), INRIA, Sophia Antipolis Cedex, B.P. 93, 06902, France aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 69/1(2006-08-01), 27-42 0920-5691 69:1<27 2006 69 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer