Showing papers by "Michihiko Minoh published in 1995"
TL;DR: A new dynamically deformable cloth model that can handle actual nonlinear kinetic properties of cloth measured by mechanical experiments is proposed, and also a numerical method appropriate for PARTY is proposed.
Abstract: A physically based environment of Artificial RealiTY for dress simulation (PARTY) which shows fully dressed humans in various environments is described. In PARTY, a dynamically deformable cloth model of a dress plays the central role. This paper proposes a new dynamically deformable cloth model that can handle actual nonlinear kinetic properties of cloth measured by mechanical experiments, and also propose a numerical method appropriate for PARTY. The numerical results of the Drape Test are compared with the shape of real cloth in experiments.
12 citations
14 Aug 1995
TL;DR: A fast algorithm for the minimum distance classifier (MDC) is proposed, which produces the same output as the exhaustive one that calculates all the distances straighforwardly and omits redundant calculations according to Karhunen-Loeve expansion.
Abstract: A fast algorithm for the minimum distance classifier (MDC) is proposed. The MDC has been used in various areas of pattern recognition because it is simple and fast compared with other complicated classifiers. The algorithm proposed is much faster than the exhaustive one that calculates all the distances straighforwardly. Our algorithm, which produces the same output as the exhaustive, omits redundant calculations according to Karhunen-Loeve expansion. From the KL-expansion of the prototype patterns, we form a subspace of the feature space, in which the order of examining the prototypes is decided adaptive to a given unknown pattern. We have applied the algorithm to recognition of handprinted Kanji characters and measured its performance on the ETL9B database. As a result, the theoretical and practical speedups were 10-20 and 4-9, respectively.
10 citations
14 Aug 1995
TL;DR: An O(n/sup 2/) time, O( n) space cluster extraction method is proposed that is faster than the ordinal clustering methods, and its clusters compare favorably with those produced by Complete Link for tightness.
Abstract: Document clustering is a powerful tool for browsing throughout a document database. Similar documents are gathered into several clusters and a representative document of each cluster is shown to users. To make users infer the content of the database from several representatives, the documents must be separated into tight clusters, in which documents are connected with high similarities. At the same time, clustering must be fast for user interaction. We propose an O(n/sup 2/) time, O(n) space cluster extraction method. It is faster than the ordinal clustering methods, and its clusters compare favorably with those produced by Complete Link for tightness. When we deal with OCR-ed documents, term loss caused by recognition faults can change similarities between documents. We also examined the effect of recognition faults to the performance of document clustering.
6 citations
TL;DR: A UNIX shell that maintains the history of not only command-lines but also “generalized command- lines” is proposed, which can detect an erroneous command-line and correct it, even if the system designer does not give such syntactic data to the system in advance.
Abstract: A UNIX shell that maintains the history of not only command-lines but also “generalized command-lines” is proposed. A generalized command-line consists of a command name and argument symbols, and represents the syntax of a command. The system can detect an erroneous command-line and correct it, even if the system designer does not give such syntactic data to the system in advance. Moreover, by analyzing the history of generalized command-lines, the system can get information useful for command-line prediction and thus achieve better prediction.
TL;DR: It is shown that the hit rate of command prediction is improved by using these indicators, which shows the effectiveness of the proposed method.
Abstract: A method of tracking the context in man-machine communication is proposed. The “tracking the context” is defined as locating the place of context switching and dividing the user's command sequence into chunks, each of which corresponds to one work. For tracking the context, “a syntactic-context” is introduced. A syntactic-context is a working set of words in the command lines a user enters. To locate the place of the syntactic-context switching, word-kind ratio and window contribution are defined. It is shown that the hit rate of command prediction is improved by using these indicators, which shows the effectiveness of the proposed method.