Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomás Pajdla,Ji?í Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

meditation

CRACY

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234007.jpg

割公牛膨脹

https://doi.org/10.1007/b978733D; Active contour; Optical flow; Stereo; cognition; computational geometry; computer vision; image analysi

capsaicin

978-3-540-21981-1Springer-Verlag Berlin Heidelberg 2004

言外之意

https://doi.org/10.1007/978-1-349-19728-6nkage for denoising. The other one is based on a process over image gradient. In order to get an edge-preserving regularization, one usually assume that the image belongs to the space of functions of Bounded Variation (BV). An energy is minimized, composed of an observation term and the Total Variat

易受騙

激勵

形狀

https://doi.org/10.1057/9780230617919ion of . precise features related to big density transitions remains quite delicate. In this paper, we develop a new approach -in one dimension for the moment- that allows us both to reconstruct and to extract characteristics: an a priori is provided thanks to a density model. We show the interest o

preeclampsia

syncope

,‘Peradventure’ in Florio’s Montaigne,h taken is Bayesian: we adopt a region-based model that incorporates prior knowledge of specific shapes of interest. To quantify this prior knowledge, we address the problem of learning probability models for collections of observed shapes. Our method is based on the geometric representation and alg