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A complete face authentication system integrating both two-dimensional (color or intensity) and three-dimensional (3-D) range data based on a low-cost 3-D sensor capable of real-time acquisition of 3-D and color images is developed. The well-known embedded hidden Markov model technique for face authentication is applied to depth maps and color images and the experimental results demonstrate significant gains resulting from the combined use of depth and color or intensity information.

In this paper a temporal learning-filtering procedure is applied to refine the left ventricle (LV) boundary detected by an active-contour model. Instead of making prior assumptions about the LV shape or its motion, this information is incrementally gathered directly from the images and is exploited to achieve more coherent segmentation. A Hough transform technique is used to find an initial approximation of the object boundary at the first frame of the sequence. Then, an active-contour model is used in a coarse-to-fine framework, for the estimation of a noisy LV boundary. The PCA transform is applied to form a reduced ordered orthonormal basis of the LV deformations based on a sequence of noisy boundary observations. Then this basis is used to constrain the motion of the active contour in subsequent frames, and thus provide more coherent identification. Results of epicardial boundary identification in B-mode images are presented. Index Terms - Echocardiography, tracking.

An object-based stereo image coding algorithm is proposed. The algorithm relies on modeling of the object structure using 3-D wire-frame models and motion estimation using globally rigid and locally deformable motion models. Algorithms for the estimation of motion and structure parameters from stereo images are described. Motion parameters are used to construct predicted images by mapping the image texture on the object surface. Coding of object parameters, appearing background regions, and prediction errors are investigated, and experimental results with standard stereo image sequences depicting general scenes are presented. The proposed algorithm is seen to be very efficient for applications such as stereoscopic video transmission. Furthermore, it is especially well suited to advanced applications such as generation and transmission of intermediate views for multiview receiver systems and applications in which objectwise editing of the bit stream is required. The latter include video production using preanalyzed scenes and virtual reality applications. Index Terms - 3-D models, object-based coding, stereo sequences.

Six optimal algorithms for the hierarchical decomposition of wire-frame surfaces that are produced by box-splines are presented. The algorithms were applied to combinations of box-spline generated meshes to compare their efficiency for the progressive coding of 3-D surfaces. Results showed that although some algorithms were simpler, no significant differences in computing time were observed.

This paper presents an algorithm for the estimation of the motion of textured objects undergoing nonrigid deformations over a sequence of images. An active mesh model, which is a finite-element deformable membrane, is introduced in order to achieve efficient representation of global and local deformations. The mesh is constructed using an adaptive triangulation procedure that places more triangles over high detail areas. Through robust least squares techniques and modal analysis, efficient estimation of global object deformations is achieved, based on a set of sparse displacement measurements. A local warping procedure is then applied to minimize the intensity matching error between subsequent images, and thus estimate local deformations. Among the major contributions of this paper are novel techniques developed to acquire knowledge of the object dynamics and structure directly from the image sequence, even in the absence of prior intelligence regarding the scene. Specifically, a coarse-to-fine estimation scheme is first developed, which adapts the model to locally deforming features. Subsequently, principal components modal analysis is used to accumulate knowledge of the object dynamics. This knowledge is finally exploited to constrain the object deformation. The problem of tracking the model over time is addressed, and a novel motion-compensated prediction approach is proposed to facilitate this. A novel method for the determination of the dynamical principal axes of deformation is developed. The experimental results demonstrate the efficiency and robustness of the proposed scheme, which has many potential applications in the areas of image coding, image analysis, and computer graphics. Index Terms - Finite elements, image warping, nonrigid motion estimation.