Stefano Casadei

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The proliferation of mobile devices and the emergence of wireless location-based services has generated consumer demand for availability of GPS in urban and indoor environments. This demand calls for enhanced GPS algorithms that accommodate high degrees of signal attenuation and multipath effects unique to the ''urban channel.'' This paper overviews the(More)
The problem of edge detection is viewed as a hierarchy of detection problems where the geometric objects to be detected (e.g. edge points, curves, regions) have increasing complexity and spatial extent. An early stage of the proposed hierarchy consists in detecting the regular portions of the visible edges. The input to this stage is given by a graph whose(More)
EEcient edge detection algorithms such as Canny's fail near curve singularities. Moreover, the standard linking algorithms used on top of these detectors often fail because of instabilities in the tracking process (due to multiple responses to the same edge and interference of nearby edges). We propose a hierarchical approach to edge detection based on a(More)
Conventional edge linking methods perform poorly when multiple responses to the same edge, bifurcations and nearby edges are present. We propose a scheme for curve inference where divergent bifur-cations are initially suppressed so that the smooth parts of the curves can be computed more reliably. Recovery of curve singularities and gaps is deferred to a(More)
We address the problem of scale selection in texture analysis. Two diierent scale parameters, feature scale and statistical scale, are de-ned. Statistical scale is the size of the regions used to compute averages. We deene the class of homogeneous random functions as a model of texture. A dishomogeneity function is deened and we prove that it has useful(More)
The problem of estimating scene contours by means of perceptual organization is formulated in a probabilistic fashion. The goal of estimation is to compute a set of contour descriptors which approximate every scene contour with high probability. A hierarchy of contour descriptors designed for this purpose is proposed. Computation at each level of the(More)
Perceptual organization provides an intermediate representation of data by means of object-and goal-independent information. The lack of complete information makes perceptual organization an in-trinsically ambiguous process which invalidates the uniqueness assumption and requires instead the generation of multiple solutions. This raises the issue of(More)
The problem of estimating the regular and visible portions of the contours in an image is formulated in a probabilistic and multiscale framework. The objective is to compute a small set of polygonal lines which, with high probability, contains an approximation to every regular visible contour in the scene. These polygonal lines are represented by paths in a(More)
—A large portion of image contours is characterized by local properties such as sharp variations of the image intensity across the contour. The integration of local image descriptors estimated by using these local properties into curvilinear descriptors is a difficult problem from a theoretical viewpoint because of the combinatorially large number of(More)
We study the problem of image segmentation in the presence of texture information at several scales. We propose to model homogeneous textured regions as ergodic random functions and to model images as piecewise ergodic random functions. Image properties can then be retrieved by ltering the image at all scale of resolution with a bunch of image descriptors(More)