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Abstract-The transmission of JPEG2000 images over wireless channels is examined using reorganization of the compressed images into error-resilient, product-coded streams. The product-code consists of Turbo-codes and Reed-Solomon codes which are optimized using an iterative process. The generation of the stream to be transmitted is performed directly using compressed JPEG2000 streams. The resulting scheme is tested for the transmission of compressed JPEG2000 images over wireless channels and is shown to outperform other algorithms which were recently proposed for the wireless transmission of images.

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Abstract. Annotations of multimedia documents typically have been pursued in two different directions. Either previous approaches have focused on low level descriptors, such as dominant color, or they have focused on the content dimension and corresponding annotations, such as person or vehicle. In this paper, we present a software environment to bridge between the two directions. M-OntoMat-Annotizer allows for linking low level MPEG-7 visual descriptions to conventional Semantic Web ontologies and annotations. We use M-OntoMatAnnotizer in order to construct ontologies that include prototypical instances of high-level domain concepts together with a formal specification of corresponding visual descriptors. Thus, we formalize the interrelationship of high-and low-level multimedia concept descriptions allowing for new kinds of multimedia content analysis and reasoning.

An object-based coding scheme is proposed for the coding of a stereoscopic image sequence, using motion and disparity information. A hierarchical block-based motion estimation approach is used for initialization, while disparity estimation is performed using a pixel-based hierarchical dynamic programming algorithm. A split and merge segmentation procedure based on 3-D motion modeling is then used to determine regions with similar motion parameters. The segmentation part of the algorithm is interleaved with the estimation part in order to optimize the coding performance of the procedure. Furthermore, a technique is examined for propagating the segmentation information with time. A 3-D motion compensated prediction technique is used for both intensity and depth image sequence coding. Error images and depth maps are encoded using DCT and Huuman methods. Alternately , an ecient wireframe depth modeling technique may b e u s e d t o c o n vey depth information to the receiver. Motion and wireframe model parameters are then quantized and transmitted to the decoder, along with the segmentation information. As a straightforward application, the use of the depth map information for the generation of intermediate views at the receiver is also discussed. The performance of the proposed compression methods is evaluated experimentally and is compared to other stereoscopic image sequence coding schemes.

Abstract-The performance of automatic 3-D face recognition can be significantly improved by coping with the nonrigidity of the facial surface. In this paper, we propose a geodesic polar parameterization of the face surface. With this parameterization, the intrinsic surface attributes do not change under isometric deformations and, therefore, the proposed representation is appropriate for expression-invariant 3-D face recognition. We also consider the special case of an open mouth that violates the isometry assumption and propose a modified geodesic polar parameterization that also leads to invariant representation. Based on this parameterization, 3-D face recognition is reduced to the classification of expression-compensated 2-D images that can be classified with state-of-the-art algorithms. Experimental results verify theoretical assumptions and demonstrate the benefits of the geodesic polar parameterization on 3-D face recognition.