Efficient many-to-many feature matching under the l1 norm
نویسندگان
چکیده
منابع مشابه
Efficient many-to-many feature matching under the l1 norm
Please cite this article in press as: M.F. Demirci e doi:10.1016/j.cviu.2010.12.012 Matching configurations of image features, represented as attributed graphs, to configurations of model features is an important component in many object recognition algorithms. Noisy segmentation of images and imprecise feature detection may lead to graphs that represent visually similar configurations that do ...
متن کاملMany-to-Many Feature Matching in Object Recognition
One of the bottlenecks of current recognition (and graph matching) systems is their assumption of one-to-one feature (node) correspondence. This assumption breaks down in the generic object recognition task where, for example, a collection of features at one scale (in one image) may correspond to a single feature at a coarser scale (in the second image). Generic object recognition therefore req...
متن کاملEfficient Many-To-Many Point Matching in One Dimension
[email protected] 2 Department of Computer Science, Villanova University, Villanova, USA. e-mail: [email protected] 3 Departament de Matemàtica Aplicada II, Universitat Politècnica de Catalunya, Barcelona, Spain. Partially supported by projects MCYT BFM2003-00368, MEC MTM2006-01267 and Gen. Cat. 2005SGR00692. e-mail: [email protected] 4 Chercheur qualifié du FNRS, Département d...
متن کاملMany-to-Many Graph Matching
Postcode 06560 City Sogutozu State Ankara Country Turkey Author Degree Dr.
متن کاملMany-to-Many Matching Design∗
We study second-degree price discrimination in markets where the product traded by the monopolist is access to other agents. We derive necessary and suffi cient conditions for the welfareand the profit-maximizing mechanisms to employ a single network or a menu of non-exclusive networks. We characterize the optimal matching schedules under a wide range of preferences, derive implications for pri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computer Vision and Image Understanding
سال: 2011
ISSN: 1077-3142
DOI: 10.1016/j.cviu.2010.12.012