{"title":"Improved FingerCode Matching Function","authors":"Gustavo de Sa, R. Lotufo","doi":"10.1109/SIBGRAPI.2006.25","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2006.25","url":null,"abstract":"FingerCode is a fingerprint correlation matching scheme that relies on texture information. In this scheme, the oriented components are extracted from a fingerprint image using a bank of Gabor filters, and a directional texture feature vector is computed for each oriented component. The feature vectors from the input and template images are compared and a matching score is obtained. Here, we explore ways to improve the matching score for the FingerCode method by using more complex matching functions. The best results were obtained by applying a nonlinear function to the texture values and weighting the texture vectors based on the spatial distribution","PeriodicalId":253871,"journal":{"name":"2006 19th Brazilian Symposium on Computer Graphics and Image Processing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127665043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Euclidean homotopic skeleton based on critical kernels","authors":"M. Couprie, A. Saúde, Gilles Bertrand","doi":"10.1109/SIBGRAPI.2006.16","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2006.16","url":null,"abstract":"Critical kernels constitute a general framework settled in the category of abstract complexes for the study of parallel thinning in any dimension. It allows to easily design parallel thinning algorithms which produce new types of skeletons, with specific geometrical properties, while guaranteeing their topological soundness. In this paper, we demonstrate that it is possible to define a skeleton based on the Euclidean distance, rather than on the common discrete distances, in the context of critical kernels. We provide the necessary definitions as well as an efficient algorithm to compute this skeleton","PeriodicalId":253871,"journal":{"name":"2006 19th Brazilian Symposium on Computer Graphics and Image Processing","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114056568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Directing the Attention of aWearable Camera by Pointing Gestures","authors":"T. D. Campos, W. Mayol-Cuevas, D. W. Murray","doi":"10.1109/SIBGRAPI.2006.13","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2006.13","url":null,"abstract":"Wearable visual sensors provide views of the environment which are rich in information about the wearer's location, interactions and intentions. In the wearable domain, hand gesture recognition is the natural replacement for keyboard input. We describe a framework combining a coarse-to-fine method for shape detection and a 3D tracking method that can identify pointing gestures and estimate their direction. The low computational complexity of both methods allows a real-time implementation that is applied to estimate the user's focus of attention and to control fast redirections of gaze of a wearable active camera. Experiments have demonstrated a level of robustness of this system in long and noisy image sequences","PeriodicalId":253871,"journal":{"name":"2006 19th Brazilian Symposium on Computer Graphics and Image Processing","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122166243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marcos Lage, Fabiano Petronetto, Afonso Paiva, H. Lopes, T. Lewiner, G. Tavares
{"title":"Vector field reconstruction from sparse samples with applications","authors":"Marcos Lage, Fabiano Petronetto, Afonso Paiva, H. Lopes, T. Lewiner, G. Tavares","doi":"10.1109/SIBGRAPI.2006.47","DOIUrl":"https://doi.org/10.1109/SIBGRAPI.2006.47","url":null,"abstract":"We present a novel algorithm for 2D vector field reconstruction from sparse set of points-vectors pairs. Our approach subdivides the domain adaptively in order to make local piecewise polynomial approximations for the field. It uses partition of unity to blend those local approximations together, generating a global approximation for the field. The flexibility of this scheme allows handling data from very different sources. In particular, this work presents important applications of the proposed method to velocity and acceleration fields' analysis, in particular for fluid dynamics visualization","PeriodicalId":253871,"journal":{"name":"2006 19th Brazilian Symposium on Computer Graphics and Image Processing","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132922210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}