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One major obstacle for the application of multiview sequences, including 3DTV, is the extremely large amount of data associated with a multiview sequence. To enable the storage or transmission of a multiview sequence at a reasonable cost, in this paper, we present a disparity estimation method based on affine model to overcome this problem. By modeling the disparity function on each patch of the multiview...
In this paper, we propose a non-symmetry and anti-packing image representation model (NAM). NAM is a hierarchical image representation method and its aim is less data amount and faster operation. By taking a rectangle sub-pattern for example, we describe the idea of NAM. In this work, based on block-wise LS linear predictor method, a gray-coded bit-plane binary image NAM representation method is presented...
The current standard image-compression approaches rely on fairly simple predictions, using either block- or wavelet-based methods. While many more sophisticated texture-modeling approaches have been proposed, most do not provide a significant improvement in compression rate over the current standards at a workable encoding complexity level. We re-examine this area, using example-based texture prediction...
In this paper we evaluate the use of Restricted Bolzmann Machines (RBM) in the context of learning and recognizing human actions. The features used as basis are binary silhouettes of persons. We test the proposed approach on two datasets of human actions where binary silhouettes are available: ViHASi (synthetic data) and Weizmann (real data). In addition, on Weizmann dataset, we combine features based...
Discovering common shape contour is a promising topic. However, local position and scale variance always leads to the mismatch of similar contours. In this study, we propose Shift Invariant Sparse Coding HMAX (SISCHMAX)to address this problem. Shift Invariant Sparse Coding is used to learn the configuration of line responses on the output of HMAX C1 layer. And we test the proposed method on Caltech101...
Understanding and modeling the function of the neurons and neural systems are primary goal of systems neuroscience. Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes in the viewpoint of statistics. In this paper, we propose a novel sparse coding model based on structural similarity (SS_SC) for natural image feature extraction...
The image segmentation based on Markov Random Field (MRF) tries to find the maximum a posterior (MAP) global optimal solution, which describes image data relations by local correlations. Comparing with the Simulated Annealing (SA) that is used in the canonical MRF, Genetic Algorithm (GA) has been applied into the optimization computation. Currently the weights of energy function and conditional probability...
Weighted prediction (WP) is one of the new tools in H.264 for encoding scenes with brightness variations. However, a single WP model does not handle all types of brightness variations. Also, large luminance difference induced by object motions would mislead an encoder in its use of WP which results in low coding efficiency. To solve these problems, a picture-based multi-pass encoding strategy, which...
This paper introduces methods for losslessly encoding a Markov random field (MRF) with arithmetic coding. The issues are how to choose the pixel scan order and how to produce coding distributions to accompany the pixels. For an MRF based on an acyclic graph, we choose a scan consistent with the graph and use belief propagation (BP) to efficiently compute the optimal coding distributions. For an MRF...
In this paper a video coding scheme based on parametric compression of texture is proposed. Each macro block is characterized either as an edge block, or as a non edge block containing texture. The non edge blocks are coded by modeling them as an auto-regressive process (AR). By applying the AR model in spatio-temporal domain, we ensure both spatial as well as temporal consistency. Edge blocks are...
This paper proposes a new analytical method for estimating parameters of a homogeneous isotropic Potts model with an asymmetric Gibbs potential function. The model is generalized by including both pairwise and triple cliques. The maximum likelihood estimates of the cliques potentials are obtained by a further elaboration of the approximate analytical estimator proposed in. Experiments with synthetic...
This paper proposes an improved algorithm to optimize the fitness function, with which the iteration times can be efficiently reduced in simulating fabric pattern deformation when it flags in the wind. Relying on a genetic algorithm model used to its deformation, an iteration method is employed and performed when genes are substituted with positions and color values of each point on the fabric surface...
In this paper we present a video coding approach similar to texture- based methods but based on motion models. We consider motion perception properties instead of spatial texture properties of the video sequence. We integrate a motion classification algorithm to separate foreground objects containing noticeable motion from the background. These background areas are labeled as skipped areas that are...
In our recent work, an analytic power-channe/error-rate-distortion (PERD) model was developed to estimate the end-to-end distortion of power constrained portable devices in real-time video communications over bandwidth limited and lossy channels. A random mode selection scheme is implemented after obtaining optimal percentages of intra, inter and skip mode through a constrained optimization process...
Digital image/video coding standards such as JPEG, H.264 are becoming more and more important for multimedia applications. Due to the huge amount of computations, there are significant efforts to speed up the encoding process. This paper proposes a Laplacian based statistical model to predict zero-quantized DCT coefficients in JPEG and to reduce the computations of encoding process. Compared with...
For collaboration, cross-platform sharing of display content amongst desktop, laptop, handheld computers and smart phones is needed. Due to architectural and performance differences, support for sharing of display content is complex and the performance is low. By using standard media players and video stream formats we reduce or avoid several of these complexities and performance bottlenecks. We do...
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