In this paper, we address the problem of the efficient encoding of object boundaries. This problem is becoming increasingly important in applications such as content-based storage and retrieval, studio and television postproduction, and mobile multimedia applications. The MPEG-4 visual standard will allow the transmission of arbitrarily shaped video objects. The techniques developed for shape coding within the MPEG-4 standardization effort are described and compared first. A framework for the representation of shapes using their contours is presented next. Such representations are achieved using curves of various orders, and they are optimal in the rate-distortion sense. Last, conclusions are drawn

This paper proposes methods for designing, tracking and coding hierarchical 2D content-based mesh representations. The design procedure consists of constructing a fine-to-coarse hierarchy of Delaunay meshes, using image- and shape-based criteria for mesh geometry simplification. Hierarchical tracking employs a coarse-to-fine strategy with mesh-based motion vector optimization. We introduce new techniques to maintain the initial mesh hierarchy and topology during tracking by imposing certain constraints at each stage of the procedure. The hierarchical compression technique is based on a nearest-neighbor ordering of mesh node points. This ordering serves to identify the mesh boundary nodes as well as establishing spatial predictors for differential coding of node coordinates and motion vectors. The proposed hierarchical mesh representation, which has applications in object-based video manipulation, indexing, and compression, provides improved tracking performance (compared to a non-hiera...

Abstract—In this paper, we present two watermarking approaches that are robust to geometric distortions. The first approach is based on image normalization, in which both watermark embedding and extraction are carried out with respect to an image normalized to meet a set of predefined moment criteria. We propose a new normalization procedure, which is invariant to affine transform attacks. The resulting watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. The second approach is based on a watermark resynchronization scheme aimed to alleviate the effects of random bending attacks. In this scheme, a deformable mesh is used to correct the distortion caused by the attack. The watermark is then extracted from the corrected image. In contrast to the first scheme, the latter is suitable for private watermarking applications, where the original image is necessary for watermark detection. In both schemes, we employ a direct-sequence code division multiple access approach to embed a multibit watermark in the discrete cosine transform domain of the image. Numerical experiments demonstrate that the proposed watermarking schemes are robust to a wide range of geometric attacks. Index Terms—Code division multiple access (CDMA) watermarking, digital watermarking, geometric attacks, image normalization, mesh modeling, watermark resynchronization. I.

Abstract—Image retargeting aims to adapt images to displays of small sizes and different aspect ratios. Effective retargeting requires emphasizing the important content while retaining surrounding context with minimal visual distortion. In this paper, we present such an effective image retargeting method using saliency-based mesh parametrization. Our method first constructs a mesh image representation that is consistent with the underlying image structures. Such a mesh representation enables easy preservation of image structures during retargeting since it captures underlying image structures. Based on this mesh representation, we formulate the problem of retargeting an image to a desired size as a constrained image mesh parametrization problem that aims at finding a homomorphous target mesh with desired size. Specifically, to emphasize salient objects and minimize visual distortion, we associate image saliency into the image mesh and regard image structure as constraints for mesh parametrization. Through a stretch-based mesh parametrization process we obtain the homomorphous target mesh, which is then used to render the target image by texture mapping. The effectiveness of our algorithm is demonstrated by experiments. Index Terms—Image retargeting, mesh parametrization, attention model. 1

The new MPEG-4 standard will provide superior services for the user, as it introduces the video objects concept. However, there is no generic segmentation technique able to provide the segmentation maps for such a coding system. In this paper, we propose a novel mesh-based video segmentation and objects tracking algorithm with both robust motion estimation and modeling of motion discontinuities. In addition, occlusions and uncovered regions are well managed. This allows the mesh deformation without the need to process remeshing in motion occlusion regions. The spatial properties of each frame are considered to make the mesh edges fit the image contents and a temporal smoothness constraint is also implemented. The proposed algorithm is able to segment multiple objects at the same time. Some experimental results are shown. 1.

We present a 2-D mesh-based mosaic representation, consisting of an object mesh and a mosaic mesh for each frame and a #nal mosaic image, for video objects with mildly deformable motion in the presence of self and#or object-to-object #external# occlusion. Unlike classical mosaic representations where successive frames are registered using global motion models, we map the uncovered regions in the successive frames onto the mosaic reference frame using local a#ne models, i.e., those of the neighboring mesh patches. The proposed method to compute this mosaic representation is tightly coupled with an occlusion adaptive 2-D mesh tracking procedure, which consist of propagating the object mesh frame to frame, and updating of both object and mosaic meshes to optimize texture mapping from the mosaic to each instance of the object. The proposed representation has been applied to video object rendering and editing, including self trans#guration, synthetic trans#guration, and 2-D augmented reality in the presence of self and#or external occlusion. We also provide an algorithm to determine the minimum number of still views needed to reconstruct a replacement mosaic which is needed for synthetic trans#guration. Experimental results are provided to demonstrate both the 2-D mesh-based mosaic synthesis and two di#erent video object editing applications on real video sequences.

Non-uniformly sampled images represented on irregular content-based meshes are central to recent developments in image compression techniques and in efficient motion tracking. We present a general approach to the development of systematic design procedures for scalable and adaptive low level image processing operators that can be applied to such non-uniformly sampled images. We provide algorithms that use the content-based mesh to address the usually difficult issue of local operator scale selection. The operator scale is therefore automatically matched to the local scale of the image features as embodied in the mesh. In this way we are able to apply a range of operators directly to compressed images. We demonstrate the approach with the design of image derivative operators that enable image feature detection to be implemented directly on compressed images. 1.

Abstract—Two-dimensional mesh-based models provide a good alternative to motion estimation and compensation. The estimation of the best node-point motion vectors is a challenging task. To this effect, Nakaya and Harashima proposed a hexagonal matching procedure. Toklu et al. improved the hexagonal search algorithm in terms of both motion-estimation accuracy and computational complexity by employing a hierarchy of regular meshes. Recognizing the limitations of regular meshes, Van Beek et al. extended Toklu et al.’s work by utilizing content-based meshes. Here, we provide an alternative hierarchical motion-estimation method with content-based meshes where hierarchical representations are employed for both the images and the irregular meshes in order to provide further improvements in computational complexity as well as motion accuracy. The comparison results are provided with real video sequences. Index Terms—Hierarchical motion estimation, model-based coding, two-dimensional mesh, two-dimensional mesh-based motion representation, video compression. I.

A network of multi modal sensors with distributed and embedded computations is con-sidered for a video surveillance and monitoring application. Practical factors limiting the video surveillance of large areas are highlighted. A network of line-of-sight sensors and mobile-agents based computations are proposed to increase the e ectiveness. CMOS digi-tal cameras in which both sampling and quantization occur on the sensor focal plane are more suitable for this application. These cameras operate at very high video frame rates and are easily synchronized to acquire images synaptically across the entire network. Also, they feature highly localized short term memories and include some SIMD parallel computa-tions as an integral part of the image acquisition. This new framework enables distributed computation for piecewise stereovision across the camera network, enhanced spatio-temporal fusion, and super resolution imaging of steadily moving subjects. A top level description of the monitor, locate and track model of a surveillance and monitoring task is presented. A qualitative assessment of several key elements of the mobile agents based computation for tracking persistent tokens moving across the entire area is outlined. The idea is to have as