161 resultados para local feature
Fourier Analysis and Gabor Filtering for Texture Analysis and Local Reconstruction of General Shapes
Resumo:
Melt processed HTSC bulk samples usually show a high inhomogeneity. These inhomogeneities influence application-relevant properties such as the lévitation force or the trapped field. In this contribution a technique is presented which allows investigation of these inhomogeneous properties. The measurements are performed by scanning the sample surface with a small coil system and detecting the first and third harmonic of the inductive response. The critical current density jc is calculated from the measured signal using a modified critical state model. Jcdistributions yielded by this technique are shown. © 1997 IEEE.
Resumo:
We have developed a novel human facial tracking system that operates in real time at a video frame rate without needing any special hardware. The approach is based on the use of Lie algebra, and uses three-dimensional feature points on the targeted human face. It is assumed that the roughly estimated facial model (relative coordinates of the three-dimensional feature points) is known. First, the initial feature positions of the face are determined using a model fitting technique. Then, the tracking is operated by the following sequence: (1) capture the new video frame and render feature points to the image plane; (2) search for new positions of the feature points on the image plane; (3) get the Euclidean matrix from the moving vector and the three-dimensional information for the points; and (4) rotate and translate the feature points by using the Euclidean matrix, and render the new points on the image plane. The key algorithm of this tracker is to estimate the Euclidean matrix by using a least square technique based on Lie algebra. The resulting tracker performed very well on the task of tracking a human face.
Fourier analysis and gabor filtering for texture analysis and local reconstruction of general shapes
Resumo:
Since the pioneering work of Gibson in 1950, Shape- From-Texture has been considered by researchers as a hard problem, mainly due to restrictive assumptions which often limit its applicability. We assume a very general stochastic homogeneity and perspective camera model, for both deterministic and stochastic textures. A multi-scale distortion is efficiently estimated with a previously presented method based on Fourier analysis and Gabor filters. The novel 3D reconstruction method that we propose applies to general shapes, and includes non-developable and extensive surfaces. Our algorithm is accurate, robust and compares favorably to the present state of the art of Shape-From- Texture. Results show its application to non-invasively study shape changes with laid-on textures, while rendering and retexturing of cloth is suggested for future work. © 2009 IEEE.