14888347
Error Resilient Mode Decision in Scalable Video Coding
Error resilient macroblock mode decision has been extensively investigated in the literature for single-layer video coding, for which error resilient mode decision is also called as intra refresh. In this paper, we present a loss-aware rate-distortion optimized macroblock mode decision algorithm for scalable video coding, wherein more macroblock coding modes than intra and inter are involved. Thanks to the good performance, the proposed method has been adopted into the joint scalable video model by the joint video team.
2496902
Improved Error Concealment Using Scene Information
Signaling of scene information in coded bitstreams was proposed by the authors and adopted into the emerging video coding standard H.264 (also known as MPEG-4 part 10 or AVC) as a supplemental enhancement information (SEI) message. This paper proposes some improved error concealment methods for intra coded pictures and scene transition pictures using the signaled scene information. Simulation results show that the proposed methods outperform conventional techniques significantly.
47345540
Shape Fitting with Outliers
Given a set $\mathcal{H}$ of n hyperplanes in ${\Bbb R}^d$, we present an algorithm that $\eps$-approximates the extent between the top and bottom k levels of the arrangement of $\mathcal{H}$ in time $O(n + (k/\eps)^c)$, where c is a constant depending on d. The algorithm relies on computing a subset of $\mathcal{H}$ of size $O(k/\eps^{d-1})$, in near linear time, such that the k-level of the arrangement of the subset approximates that of the original arrangement. Using this algorithm, we propose efficient approximation algorithms for shape fitting with outliers for various shapes. These are the first algorithms to handle outliers efficiently for the shape fitting problems considered.
17258193
Spatiotemporal video segmentation based on graphical models
This paper proposes a probabilistic framework for spatiotemporal segmentation of video sequences. Motion information, boundary information from intensity segmentation, and spatial connectivity of segmentation are unified in the video segmentation process by means of graphical models. A Bayesian network is presented to model interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notion of the Markov random field is used to encourage the formation of continuous regions. Given consecutive frames, the conditional joint probability density of the three fields is maximized in an iterative way. To effectively utilize boundary information from the intensity segmentation, distance transformation is employed in local objective functions. Experimental results show that the method is robust and generates spatiotemporally coherent segmentation results. Moreover, the proposed video segmentation approach can be viewed as the compromise of previous motion based approaches and region merging approaches.
5135938
Privacy preserving database application testing
Traditionally, application software developers carry out their tests on their own local development databases. However, such local databases usually have only a small number of sample data and hence cannot simulate satisfactorily a live environment, especially in terms of performance and scalability testing. On the other hand, the idea of testing applications over live production databases is increasingly problematic in most situations primarily due to the fact that such use of live production databases has the potential to expose sensitive data to an unauthorized tester and to incorrectly update information in the underlying database. In this paper, we investigate techniques to generate mock databases for application software testing without revealing any confidential information from the live production databases. Specifically, we will design mechanisms to create the deterministic rule set R, non-deterministic rule set N R, and statistic data set S for a live production database. We will then build a security Analyzer which will process the triplet <R',N R',S'> together with security requirements (security policy) and output a new triplet <R',N R',S'> The security Analyzer will guarantee that no confidential information could be inferred from the new triplet <R',N R',S'> The mock database generated from this new triplet can simulate the live environment for testing purpose, while maintaining the privacy of data in the original database.
5958340
Cyclone: A Safe Dialect of C
Cyclone is a safe dialect of C. It has been designed from the ground up to prevent the buffer overflows, format string attacks, and memory management errors that are common in C programs, while retaining C’s syntax and semantics. This paper examines safety violations enabled by C’s design, and shows how Cyclone avoids them, without giving up C’s hallmark control over low-level details such as data representation and memory management.
10282937
Decoding Algorithm in Statistical Machine Translation
Decoding algorithm is a crucial part in statistical machine translation. We describe a stack decoding algorithm in this paper. We present the hypothesis scoring method and the heuristics used in our algorithm. We report several techniques deployed to improve the performance of the decoder. We also introduce a simplified model to moderate the sparse data problem and to speed up the decoding process. We evaluate and compare these techniques/models in our statistical machine translation system.