Arbitrarily shaped video-object coding by wavelet
Video-object coding is one of the most important functionalities proposed by MPEG-4. We propose a new wavelet method to encode the texture of an arbitrarily shaped object, both for the still and for the video-object. The method uses the shape adaptive wavelet transform (SA-DWT) in MPEG-4 still object coding, but with a computationally more efficient lifting implementation. The transformed object coefficients are then quantized and entropy encoded with a partial bit-plane embedded coder, which greatly improves the coding efficiency. We denote the coding algorithm as the video-object wavelet (VOW) coder. Experimental results show that VOW significantly outperforms MPEG-4 in still-object coding, and achieves a comparable performance in video-object coding in terms of PSNR. Moreover, the VOW decoded object looks better subjectively, with less annoying blocking artifacts than that of MPEG-4.

title: On the compression and streaming of concentric mosaic data for free wandering in a realistic environment over the Internet
abstract: In this paper, we describe a system for wandering in a realistic environment over the Internet. The environment is captured by the concentric mosaic, compressed via the reference block coder (RBC), and accessed and delivered over the Internet through the virtual media (Vmedia) access protocol. One of the key contributions of the paper is the proposal of the RBC concentric mosaic coder. The RBC coder not only compresses the huge dataset of the concentric mosaic very efficiently, but also produces a well-organized bitstream that can be accessed just-in-time (JIT). To reconstruct a virtual view, only a portion of the RBC bitstream needs to be accessed and decoded. This greatly reduces the memory and computation requirement of the viewer compared with first decoding the entire concentric mosaic data set and then rendering from the decoded data. Our second contribution is the employment of the Vmedia protocol to deliver the compressed concentric mosaic bitstream just-in-time over the Internet. Only the bitstream segments corresponding to the current view are streamed over the Internet. The delivered bitstream segments are managed by a local Vmedia cache, so that frequently used bitstream segments do not need to be streamed over the Internet repeatedly, and a RBC bitstream larger than the memory capacity can be easily handled. Combining RBC and Vmedia, a concentric mosaic interactive browser is developed through which the user can freely wander in a realistic environment, e.g., rotate around, walk forward/backward, and sidestep, even under a tight bandwidth.

title: The seamlessly multiplexed embedded codec (SMEC) and its application in image coding
abstract: The landmark JPEG 2000 image compression standard offers not only superior compression performance, but also incredible flexibility. The compressed bitstream of JPEG 2000 can be flexibly reorganized to another bitstream of different bitrate, resolution, and spatial region of interest (ROI) or a combination of any of the above. Such flexibility is achieved by multiplexing the compressed bitstream pieces of multiple code-blocks together into a combined bitstream, with the length of the code-block bitstream piece (LOCB) embedded in the combined bitstream. The LOCB serves both to reorganize the bitstream, and to decode the bitstream. It represents a significant overhead, especially since there is no correlation between the neighbor LOCBs. In this work, we introduce seamless multiplexing, and separate the information needed for the reorganization, i.e., the LOCB, from the compressed bitstream itself by using the decoder pointer to multiplex the bitstream pieces. As a result, the compressed bitstream consists of code-block bitstream pieces seamlessly concatenated to each other. With seamless multiplexing, only the compressed bitstream (without LOCB) needs to be delivered to the receiving client. It results in better compression performance and higher granularity of access. Another benefit of seamless multiplexing is that the relative coding orders of the code-blocks are preserved in the bitstream reorganization. As a result, the seamlessly multiplexed embedded codec (SMEC) may utilize the dependencies among the code-blocks in the coding, thus further boost the compression performance.

title: Motion compensated lifting wavelet and its application in video coding
abstract: A motion compensated lifting (MCLIFT) framework is proposed for the 3D wavelet video coder. By using bi-directional motion compensation in each lifting step of the temporal direction, the video frames are effectively de-correlated. With proper entropy coding and bitstream packaging schemes, the MCLIFT wavelet video coder can be scalable in frame rate and quality level. Experimental results show that the MCLIFT video coder outperforms the 3D wavelet video coder with the same entropy coding scheme by an average of 1.1-1.6dB, and outperforms MPEG-4 coder by an average of 0.9-

title: An embedded still image coder with rate-distortion optimization
abstract: It is well known that the fixed rate coder achieves optimality when all coefficients are coded with the same rate-distortion (R-D) slope. In this paper, we show that the performance of the embedded coder can be optimized in a rate-distortion sense by coding the coefficients with decreasing R-D slope. We denote such a coding strategy as rate-distortion optimized embedding (RDE). RDE allocates the available coding bits first to the coefficient with the steepest R-D slope, i.e., the largest distortion decrease per coding bit. The resultant coding bitstream can be truncated at any point and still maintain an optimal R-D performance. To avoid the overhead of coding order transmission, we use the expected R-D slope, which can be calculated from the coded bits and is available in both the encoder and the decoder. With the probability estimation table of the QM-coder, the calculation of the R-D slope can be just a lookup table operation. Experimental results show that the rate-distortion optimization significantly improves the coding efficiency in a wide bit rate range.

title: Distributed hosting of Web content with erasure coding and unequal weight assignment
abstract: By sharing and hosting personal Web content in a peer-to-peer (P2P) fashion, we may increase the bandwidth of retrieval and improve the reliability of retrieval. The cost is that the Web content has to be replicated to and stored in the peers, consuming valuable network bandwidth and peer storage space. In this work, we develop two technologies, namely hierarchical content organization with unequal weight assignment and erasure coding, to reduce the amount of content to be distributed, yet still maintain the retrieval speed up and reliability. Significant improvement over the ordinary Web server is demonstrated.

title: Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures
abstract: Individual privacy will be at risk if a published data set is not properly de-identified. k-anonymity is a major technique to de-identify a data set. A more general view of k-anonymity is clustering with a constraint of the minimum number of objects in every cluster. Most existing approaches to achieving k-anonymity by clustering are for numerical (or ordinal) attributes. In this paper, we study achieving k-anonymity by clustering in attribute hierarchical structures. We define generalisation distances between tuples to characterise distortions by generalisations and discuss the properties of the distances. We conclude that the generalisation distance is a metric distance. We propose an efficient clustering-based algorithm for k-anonymisation. We experimentally show that the proposed method is more scalable and causes significantly less distortions than an optimal global recoding k-anonymity method.

title: Construct robust rule sets for classification
abstract: We study the problem of computing classification rule sets from relational databases so that accurate predictions can be made on test data with missing attribute values. Traditional classifiers perform badly when test data are not as complete as the training data because they tailor a training database too much. We introduce the concept of one rule set being more robust than another, that is, able to make more accurate predictions on test data with missing attribute values. We show that the optimal class association rule set is as robust as the complete class association rule set. We then introduce the k-optimal rule set, which provides predictions exactly the same as the optimal class association rule set on test data with up to k missing attribute values. This leads to a hierarchy of k-optimal rule sets in which decreasing size corresponds to decreasing robustness, and they all more robust than a traditional classification rule set. We introduce two methods to find k-optimal rule sets, i.e. an optimal association rule mining approach and a heuristic approximate approach. We show experimentally that a k-optimal rule set generated by the optimal association rule mining approach performs better than that by the heuristic approximate approach and both rule sets perform significantly better than a typical classification rule set (C4.5Rules) on incomplete test data.

title: Improved Squeaky Wheel Optimisation for Driver Scheduling
abstract: This paper presents a technique called Improved Squeaky Wheel Optimisation (ISWO) for driver scheduling problems. It improves the original Squeaky Wheel Optimisation's (SWO) effectiveness and execution speed by incorporating two additional steps of Selection and Mutation which implement evolution within a single solution. In the ISWO, a cycle of Analysis-Selection-Mutation-Prioritization-Construction continues until stopping conditions are reached. The Analysis step first computes the fitness of a current solution to identify troublesome components. The Selection step then discards these troublesome components probabilistically by using the fitness measure, and the Mutation step follows to further discard a small number of components at random. After the above steps, an input solution becomes partial and thus the resulting partial solution needs to be repaired. The repair is carried out by using the Prioritization step to first produce priorities that determine an order by which the following Construction step then schedules the remaining components. Therefore, the optimisation in the ISWO is achieved by solution disruption, iterative improvement and an iterative constructive repair process performed. Encouraging experimental results are reported.

title: A scalable semantic routing architecture for grid resource discovery
abstract: Grids technology enables the sharing and collaborating of wide variety of resources. To fully utilize these resources, effective discovery techniques are necessities. However, the complicated and heterogeneous characteristics of the grid resource make sharing and discovering a challenging issue. In this paper, we propose a comprehensive semantic-based resource discovery framework, which performs an effective searching according to the semantic properties of what is searched. In the framework, nodes are grouped into clusters according to some criteria. Resources are indexed and aggregated with a highly compressed format. The summarized index can act as network knowledge to guide routing in the network. Intra-cluster and inter-cluster routing strategies are proposed to support scalable and efficient searching. Results from simulation demonstrate that this architecture is very effective in grid resource discovery.

title: Accelerating XML Structural Join by Partitioning
abstract: Structural join is the core part of XML queries and has a significant impact on the performance of XML queries, several classical structural join algorithms have been proposed such as Stack-tree join and XR-Tree join. In this paper, we consider to answer the problem of structural join by partitioning. We first extend the relationships between nodes to the relationships between partitions in the plane and get some observations. We then propose a new partition-based method P-Join for structural join. Based on P-Join, moreover, we present an enhanced partitioned-based spatial structural join algorithm PSSJ.