This paper presents a crowd modelling method in Collaborative Virtual Environment (CVE) which aims to create a sense of group presence to provide a more realistic virtual world. An adaptive display is also presented as a key element to optimise the needed information to keep an acceptable frame rate during crowd visualisation. This system has been integrated in the several CVE platforms which will be presented at the end of this paper. 1.1 Keywords Autonomous agents, virtual crowds, virtual environments.

We discuss representations of prefix codes and the corresponding storage space and decoding time requirements. We assume that a dictionary of words to be encoded has been defined and that a prefix code appropriate to the dictionary has been constructed. The encoding operation becomes simple given these assumptions and given an appropriate parsing strategy, therefore we concentrate on decoding. The application which led us to this work constrains the use of internal memory during the decode operation. As a result, we seek a method of decoding which has a small memory requirement. Introduction Data compression is an important and much-studied problem. Compressing data to be stored or transmitted can result in significant improvements in the use of computing resources. The degree of improvement that can be achieved depends not only on the selection of a data compression method, but also on the characteristics of the particular application. That is, no single data compression algorithm wi...

This doctoral dissertation presents a range of results concerning efficient algorithms and data structures for string processing, including several schemes contributing to sequential data compression. It comprises both theoretic results and practical implementations. We study the suffix tree data structure, presenting an efficient representation and several generalizations. This includes augmenting the suffix tree to fully support sliding window indexing (including a practical implementation) in linear time. Furthermore, we consider a variant that indexes naturally word-partitioned data, and present a linear-time construction algorithm for a tree that represents only suffixes starting at word boundaries, requiring space linear in the number of words. By applying our sliding window indexing techniques, we achieve an efficient implementation for dictionary-based compression based on the LZ-77 algorithm. Furthermore, considering predictive source

: Bitmaps are data structures occurring often in information retrieval. They are useful; they are also large and expensive to store. For this reason, considerable effort has been devoted to finding techniques for compressing them. These techniques are most effective for sparse bitmaps. We propose a preprocessing stage, in which bitmaps are first clustered and the clusters used to transform their member bitmaps into sparser ones, that can be more effectively compressed. The clustering method efficiently generates a graph structure on the bitmaps. In some situations, it is desired to impose restrictions on the graph; finding the optimal graph satisfying these restrictions is shown to be NPcomplete. The results of applying our algorithm to the Bible is presented: for some sets of bitmaps, our method almost doubled the compression savings. 1. Introduction Textual Information Retrieval Systems (IRS) are voracious consumers of computer storage resources. Most conspicuous, of course, is the...

Greedy off-line textual substitution refers to the following approach to compression or structural inference. Given a long textstring x, a substring w is identified such that replacing all instances of w in x except one by a suitable pair of pointers yields the highest possible contraction of x; the process is then repeated on the contracted textstring until substrings capable of producing contractions can no longer be found. This paper examines computational issues arising in the implementation of this paradigm and describes some applications and experiments.

Test data compression and test resource partitioning (TRP) are necessary to reduce the volume of test data for system-on-a-chip designs. We present a new class of variable-to-variable-length compression codes that are designed using distributions of the runs of 0s in typical test sequences. We refer to these as frequency-directed run-length (FDR) codes. We present experimental results for ISCAS 89 benchmark circuits and two IBM production circuits to show that FDR codes are extremely effective for test data compression and TRP. We derive upper and lower bounds on the compression expected for some generic parameters of the test sequences. These bounds are especially tight when the number of runs is small, thereby showing that FDR codes are robust, i.e., they are insensitive to variations in the input data stream. In order to highlight the inherent superiority of FDR codes, we present a probabilistic analysis of data compression for a memoryless data source. Finally, we derive entropy bounds for the benchmark test sets and show that the compression obtained using FDR codes is close to the entropy bounds.

This paper presents two simple approximation algorithms for the shortest superstring problem, with approximation ratios 2 2 3 ( 2:67) and 2 25 42 ( 2:596), improving the best previously published 2 3 4 approximation. The framework of our improved algorithms is similar to that of previous algorithms in the sense that they construct a superstring by computing some optimal cycle covers on the distance graph of the given strings, and then break and merge the cycles to finally obtain a Hamiltonian path, but we make use of new bounds on the overlap between two strings. We prove that for each periodic semi-infinite string ff = a1a2 \Delta \Delta \Delta of period q, there exists an integer k, such that for any (finite) string s of period p which is inequivalent to ff, the overlap between s and the rotation ff[k] = ak ak+1 \Delta \Delta \Delta is at most p+ 1 2 q. Moreover, if p q, then the overlap between s and ff[k] is not larger than 2 3 (p+q). In the previous shortes...

We give a new text compression scheme based on Forbidden Words ("antidictionary"). We prove that our algorithms attain the entropy for equilibrated binary sources. One of the main advantage of this approach is that it produces very fast decompressors. A second advantage is a synchronization property that is helpful to search compressed data and to parallelize the compressor. Our algorithms can also be presented as "compilers" that create compressors dedicated to any previously fixed source. The techniques used in this paper are from Information Theory and Finite Automata; as a consequence, this paper shows that Formal Language Theory (in particular Finite Automata Theory) can be useful in Data Compression. Keywords: data compression, information theory, finite automaton, forbidden word, pattern matching. 1 Introduction We present a simple text compression method called DCA (Data Compression with Antidictionaries) that uses some "negative" information about the text, which is describe...

: The emergence of the CD-ROM as a storage medium for full-text databases raises the question of the maximum size database that can be contained by this medium. As an example, the problem of storing the Tr'esor de la Langue Fran¸caise on a CD-ROM is examined in this paper. The text alone of this database is 700 MB long, more than a CD-ROM can hold. But in addition the dictionary and concordance needed to access this data must be stored. A further constraint is that some of the material is copyrighted, and it is desirable that such material be difficult to decode except through software provided by the system. Pertinent approaches to compression of the various files are reviewed and the compression of the text is related to the problem of data encryption: specifically, it is shown that, under simple models of text generation, Huffman encoding produces a bit-string indistinguishible from a representation of coin flips. Categories and Subject Descriptors: E.3 E.4 H.3.2 J.5 General terms: ...

This paper addresses the architectural dependencies in the design of the system and evaluates performance of the implementation. The new version, MIRAGE + , performs well compared to Mirage even though eight times the amount of data is sent on each page fault because of the larger page size used in the implementation. We show that performance of systems with a large page size to network packet size can be dramatically improved on conventional hardware by applying three well-known techniques: packet blasting, compression, and running at interrupt level