20150121
Joint texture-shape optimization for MPEG-4 multiple video objects
In this paper, we present a uniform framework for optimal multiple video object bit allocation in MPEG-4. We combine the rate-distortion (R-D) models for the texture and shape information of arbitrarily shaped video objects to develop the joint texture-shape R-D models. The dynamic programming technique is applied to optimize the bit allocation for the multiple video objects. The simulation results demonstrate that the proposed joint texture-shape optimization algorithm outperforms the MPEG-4 verification model on the decoded picture quality.
27700138
Improved single-video-object rate control for MPEG-4
Rate control plays a central role in constant bit-rate video coding applications using MPEG-4. This paper considers single-video-object rate control for MPEG-4 and presents a new rate-control algorithm based on the quadratic rate-distortion (R-D) model. The major innovations are a novel constraint for the least-mean-square estimation of the model parameters of the R-D function, a new measure for the encoding complexity, novel quantizer control and an efficient frame skipping strategy. Simulation results show that the MPEG-4 coder, using the proposed algorithm, can achieve a higher PSNR than a coder using the conventional rate-control algorithm.
52859343
Towards rate-distortion tradeoff in real-time color video coding
In this paper, we address to the key problem in real-time video coding, the rate-distortion tradeoff. We found that the distribution of the integer transform coefficients in H.264 color video coding can be approximated by Laplacian distribution but the rate-distortion characteristics should be modelled for the luminance and chrominance components separately. So we propose separable rate-distortion models for color video coding. The feedback from the encoder buffer is analyzed by a control-theoretic adaptation approach. To achieve smooth video quality and satisfy the delay constraints in real-time applications, a novel rate distortion tradeoff controller is employed. Simulations results demonstrate that the proposed approach can achieve smooth video quality without sacrificing overall quality while efficiently utilize the bandwidth without buffer overflow or underflow.
40433168
Linear rate-distortion models for MPEG-4 shape coding
In this letter, we explore the rate-distortion (R-D) characteristics of binary shape information in the MPEG-4 standard. The shape coding scheme is a block-based context-based arithmetic encoding approach and distortion is introduced by down and up sampling. Generally, the shape bit rate and nonnormalized distortion increase in proportion with the number of border blocks. At any given resolution scale, the more complex an object, the more distortion that is introduced. Consequently, we propose an R-D model based on the parameters derived from the border blocks and a block-based shape complexity for the video object. The computational complexity is much lower than other existing methods. Experimental results show that it can accurately predict the bit rate and distortion of the binary shape for rate control purposes.
204993527
The size of graphs with clique number m and without nowhere-zero 4-flows
Abstract Let G be a 2-edge-connected simple graph on n ⩾24 vertices containng no K m +1. Of |E(G)|⩾( n - 17 - k 2 )+(m - l)( k + 1 2 )+ 33, where ⌊ n −17/ m ⌋, then either G has a nowhere-zero 4-flow, or G can be contracted to the Petersen graph. This is a generalization of a result in [4].
8890999
A unified framework for clustering heterogeneous Web objects
We introduce a novel framework for clustering Web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a unified feature space, their flexibilities to explore and adjust contributing effects from different heterogeneous information are compromised. In contrast, our framework enables separate clustering of homogeneous data in the entire process based on their respective features, and a layered structure with link information is used to iteratively project and propagate the clustered results between layers until it converges. Our experimental results show that such a scheme not only effectively overcomes the problem of data sparseness caused by the high dimensional link space but also improves the clustering accuracy significantly. We achieve 19% and 41% performance increases when clustering Web-pages and users based on a semi-synthetic Web log. Finally, we show a real clustering result based on UC Berkeley's Web log.
6802371
Improving web search results using affinity graph
In this paper, we propose a novel ranking scheme named Affinity Ranking (AR) to re-rank search results by optimizing two metrics: (1) diversity -- which indicates the variance of topics in a group of documents; (2) information richness -- which measures the coverage of a single document to its topic. Both of the two metrics are calculated from a directed link graph named Affinity Graph (AG). AG models the structure of a group of documents based on the asymmetric content similarities between each pair of documents. Experimental results in Yahoo! Directory, ODP Data, and Newsgroup data demonstrate that our proposed ranking algorithm significantly improves the search performance. Specifically, the algorithm achieves 31% improvement in diversity and 12% improvement in information richness relatively within the top 10 search results.
14828051
MRSSA: an iterative algorithm for similarity spreading over interrelated objects
We introduce the Multiple Relationship Similarity Spreading Algorithm (MRSSA) to enhance IR effectiveness. This method has similarity computed in an iterative "spreading" fashion for multiple object types, combining both inter- and intra-object relationships. We demonstrate the value of this approach in the context of the WWW, where the key objects are web pages and queries, Relationships considered are derived from hyperlinks (in- and out-links) and click-through logs.
7363283
Self-adapting software for numerical linear algebra and LAPACK for clusters
This article describes the context, design, and recent development of the LAPACK for clusters (LFC) project. It has been developed in the framework of Self-Adapting Numerical Software (SANS) since we believe such an approach can deliver the convenience and ease of use of existing sequential environments bundled with the power and versatility of highly tuned parallel codes that execute on clusters. Accomplishing this task is far from trivial as we argue in the paper by presenting pertinent case studies and possible usage scenarios.