bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scene interpretation based on boundary representations of stereo images
Authors: Sugimoto Kazuhide , Tomiya Fumiaki 
Published: July 2007

AbstractGenerally, extraction of boundary lines from a binocular stereo image is effective for a plane with patterns or a curved surface with shadows, and a place with uniform surface. Since a uniform plain cannot directly be reconstructed, however, another process to reconstruct the plain is needed after its boundary line is reconstructed. If a simple algorithm is applied to this process, a false plane is extracted sometimes. This paper describes a method uniquely to determine a plane from the three‐dimensional boundary lines of an object in the stereo image. The method is effective for any object consisting of planes in the image. The method can also locally detect a fault in the boundary line so that this makes its compensation process easy. The final output image of this method is available in a form of a ‘geometrical mode’.
Algorithms and performance evaluation of join processing on KD‐tree indexed relations
Authors: Kitsuregawa Masaru , Takagi Mikio , Harada Lilian 
Published: July 2007

AbstractThis paper proposes a new join processing algorithm for the KD‐tree indexed relations. The processing is evaluated by a simulation and the effectiveness is demonstrated. The KD‐tree index is one of the typical multidimensional clustering data structures. A flexible database can be constructed which provides uniform access characteristics in regard to the multiple attributes. On the other hand, the data structure is made complex, and the traditional join processing technique for the ordinary one‐dimensional clustering relation, which maintains the physical order, cannot be applied. Also, there has not been proposed a join technique for the KD‐tree indexed relations.This paper introduces anew the concepts called “wave” and “join range,” and proposes an efficient join algorithm for the KD‐tree indexed relations. Then an extended algorithm is proposed by introducing the garbage collection function into the forementioned basic algorithm, where the unnecessary tuples on the main memory can be eliminated dynamically. Each of those algorithms is evaluated by a simulation, and the effectiveness is verified.When the order of the join attribute is not preserved, the join processing by the hash‐based algorithm, which at present is considered the fastest, requires two read scannings and one write scanning, while the best algorithm proposed in this paper can execute the processing by almost one read scanning. Thus, a drastic improvement of the performance can be expected for the join processing by the proposed algorithm.
Priority management for concurrent execution of real‐time and on‐line transactions
Authors: Kataoka Ryoji , Satoh Tetsuji , Inoue Ushio 
Published: July 2007

AbstractThis paper presents priority management methods for concurrent execution of real‐time transactions with timing constraints and on‐line transactions without timing constraints in a real‐time database system (RTDBS). The aim of this study is the meeting of deadlines of real‐time transactions and shortening the response time of on‐line transactions at the same time. The proposed methods are Simple Mix, Biased Mix, and Balanced Mix, each of which differs in its strategy for assigning priorities to on‐line transactions. Simulation results show that Balanced Mix, which determines priorities dynamically according to the slack of real‐time transactions, can shorten the response time of on‐line transactions while keeping the deadline‐missing ratio of real‐time transactions low.
Estimation of the probability density function and aposterioriprobability by neural networks, and applications to vowel recognition
Authors: Nakagawa Seiichi , Ono Yoshiyuki 
Published: July 2007

AbstractFeed‐forward neural networks have been used for pattern recognition, because they have an ability to estimatea posterioriprobability. This paper investigates the ability to estimate thea posterioriprobability by using one‐dimensional Gaussian distributions, uniform distributions, their mixed distributions and real speech data, and applies the networks to speech recognition. Furthermore, the ability to estimate a probability density function of artificial data by using a vector quantization technique and neural networks and also to apply them to speech recognition also are investigated. Feed‐forward neural networks, radial basis function networks (RBF), Gaussian mixed distributions and multitemplate methods for speech recognition are compared. It is concluded that the vector quantization‐based RBF is the best in practice.
Recovering 3D models from silhouette sequences and detecting unexposed regions
Authors: Zheng Jiang Yu , Kishino Fumio 
Published: July 2007

AbstractThis paper recovers 3D shapes from contours for graphics display in a 3D virtual environment. In this method, a continuous sequence of images is taken as an object rotates, and smooth convex shape is estimated instantaneously from its contour and contour movement. Shapes also are analyzed that do not satisfy the conditions of smoothness and visibility, which are indispensable for modeling an object. A region that is not exposed as contour yields a non‐smoothness in the tracked contour movement. An unknown region is obtained for further investigation using other visual cues. The entire process from silhouettes to a 3D model is based on local computation; which is promising for producing shapes in real time. The direct goal is to establish 3D graphics models of human faces for the growing needs of visual communications. Some good results have been obtained.
Sign language translation based on syntactic and semantic analysis
Authors: Abe Masahiro , Sakou Hiroshi , Sagawa Hirohiko 
Published: July 2007

AbstractThe prototype sign language translation system described herein interprets Japanese sign language to verbal Japanese language. Since sign language has a unique morphology and syntax, the sign language translation system requires linguistic translation after recognition of the input symbols. One of the main difficulties in translation is a result of the insufficiency of syntactic markers in the input information.In Japanese sign language, input is represented as a sequence of important words. In our method, semantic dependency analysis based on case frame grammar is carried out to complement the lack of information such as postpositions. Then, rule‐based rephrasing is executed to obtain natural verbal language. This scheme contributes both flexibility and ease of maintenance to the translation system. A prototype sign language translation system was implemented and tested using 123 sentences extracted from a sign language textbook. Experimental results indicate that 76 percent of the sentences can be translated correctly if they have no recognition error in input sentence. However, if a recognition error occurs, the experiment indicates that the translation will become highly ambiguous. Therefore, the capability for rejecting incorrect sentences is very important, along with the capability for translating correct input sentences. Future issues include incorporation of unused information, such as facial expression, spatial information and contexts in sign language to improve translation accuracy.
Three‐dimensional object recognition using spherical correlation
Authors: Okada Takashi , Sano Mutsuo , Kaneko Hiroshi 
Published: July 2007

AbstractMost research in 3‐D object recognition has concentrated on feature extraction and paid much less attention to the computation and evaluation of matching metric for feature comparison. Many existing algorithms for object recognition have problems with noisy data and incomplete (partial) input data.This paper proposes a similarity metric based on extensive exploitation of 3‐D features and characteristics of objects to solve the shortcomings of existing algorithms. Simulation and experimental results indicate that the proposed matching metric ranks the similarities among objects consistent with human intuition. It also is robust to noise and can even predict the outcome for a given noise level. Furthermore, in occlusion cases, the proposed algorithm is capable of recognizing objects using partial (incomplete) input data. It can also be used to evaluate the reliability and the contribution of a subset of the data relative to the overall object recognition task.
Description and tracking of moving articulated objects
Authors: Kurakake Shoji , Nevatia Ramakant 
Published: July 2007

AbstractThis paper discusses the problem of deriving a description for an articulated object from images taken in the real environment. Sometimes with the articulated object, the detection of the articulation is difficult depending on the deformation or the direction of the view line. Also, the false articulation is detected due to the disconnection of the object contour derived from the image or due to the noise.To cope with such difficulties, a method is proposed for the moving articulated object, where the articulation is detected with a high reliability, and the description as well as the segmentation of the articulated object are derived by processing a series of images containing different outblocks and deformations of the object. In this method, the ribbon, which is the two‐dimensional version of the generalized cylinder, is used as the basic representation for the part. The initial description is derived from each frame image, and the initial descriptions of various frames are compared by ribbon matching to detect the articulation position with a high reliability. Based on the detected positions, the initial descriptions are integrated selectively and the final description is obtained. As a by‐product of the ribbon matching, the tracking of parts also is realized. By an experiment using a human walking scene, the usefulness of the proposed method is demonstrated.
Route description by 3D objects in panoramic representation
Authors: Li Shigang , Tsuji Saburo 
Published: July 2007

AbstractFinding landmarks autonomously for guiding longdistance navigation by a mobile robot is explored. In a trial navigation, the robot continuously views and memorizes scenes along the route. When the same route is subsequently pursued again, the robot locates and orients itself based on the memorized scene. Since the stream of images is highly redundant, it is transformed into an intermediate 2(1/2)D representation, called panoramic representation, with much less data.Although the panoramic representation can be used for guidance of the autonomous navigation, it still contains a huge amount of data for a very long route. A human memorizes only very imposing objects along the route such as an old church or a very high tower, and uses them as landmarks. The author's robot also finds distinctive objects along the route and memorizes their features as well as spatial relationships for navigation guidance. The 3D objects along the route are segmented in the panoramic representation by fusing range estimates and color attributes, and then a structure map representing their arrangement in space is yielded. To find distinctive objects used for the landmarks, the spatial relationships, shapes and color attributes of the objects are examined.
Estimating the performance of multiple functional unit and pipelined processor using statistical instruction dependencies
Authors: Kinouchi Yasuo , Hoshiko Takayuki , Inamori Kouichi 
Published: July 2007

AbstractThis paper considers the processor with the parallel operation and lookahead control functions based on the real‐time system program. The relation between the logical dependencies among instructions and the performance improvement is analyzed. With respect to the dependency, the number of dynamic steps that are processed between logically dependent instructions is considered, and the histogram is examined in the program actually run.A method is devised wherein the behavior of the processor executing the instructions following the written order is represented in terms of the probability based on the statistical data. The effects of the dependency and the number of functional units on the processor also is evaluated by a simulation. The validity of the proposed method is verified and the effect is evaluated of performance improvement when the order of instruction execution is made variable.
FISH: Flexible information sharing and handling system
Authors: Seki Yoshiaki , Yamakami Toshihiko , Shimizu Akihiro 
Published: July 2007

AbstractWith the progress of network technology and workstation technology as the background, there has been progress in the exchange/transmission of information as well as document sharing by electronic means in the office environment. At present, however, techniques have not been developed to the stage where such fragmented information as knowhow is stored/retrieved/managed in the distributed environment.From such a viewpoint, the authors have constructed the knowhow storage system FISH (flexible information sharing and handling system), which can store the knowhow in the text format. In FISH, the minimum unit decomposition of the information and the flexible structurization are realized by decomposing the knowhow into multiple virtual cards to be stored in the computer. Knowhow, which is difficult to be given a systematic structure, is managed by automatically providing links among the card based on the keywords attached to the individual cards.This paper describes first the management method for the knowhow which is the basic design of FISH. Then the features, the functions that can be used, and the implementation of the system are discussed. The result of the one‐year operation experiment of the system in the office of the authors is presented, together with discussions. Using FISH, it is made possible to store the knowhow and share the use in the distributed environment.
Built‐in current testing for CMOS logic circuits using random patterns
Authors: Yokoyama Hiroshi , Tamamoto Hideo , Narita Yuichi 
Published: July 2007

AbstractWith respect to CMOS logic circuits, it is reported that a fault can occur cannot be covered by conventional classical fault model, and the current testing is considered to be interesting as a testing method to detect such a fault.This paper proposes a fault‐detection method for the CMOS logic circuit which can detect the stuck‐at fault and the stuck‐open fault based on the dynamic power supply current observed when a pseudorandom pattern is applied as the input. A built‐in testing circuit for realizing the principle is shown. The feature of the current testing is that the fault can be detected by observing the power supply current as long as the fault in the circuit is activated, and it is not required to propagate the fault information to the output. Based on that property, a random pattern with a small test generation cost is used as the test pattern.As the test pattern, the pseudorandom pattern is generated autonomously by utilizing the output signal of the circuit under test. The fault detection is made easier by this pattern generation since the effect of the fault on the power supply current is enhanced. In determining whether or not the power supply current is that of the normal circuit, a method based on the time‐course of the power supply current is used, with the power supply currents for various test patterns as the feature parameter. The proposed procedure is evaluated by a simulation, and the usefulness of the proposed method is demonstrated.
Realtime parallel and cooperative recognition of human face for a naturalistic visual human interface
Authors: Hasegawa Osamu , Ishizuka Mitsuru , Yokosawa Kazuhiko 
Published: July 2007

AbstractThe concept of a Visual Software Agent (VSA), i.e., an anthropomorphic agent possessing a realistic human form and communication functions that create an interface with the user, is proposed. Research is proceeding on its implementation on a parallel computer. In this paper, we describe a method that is effective as the visual input function of the anthropomorphic agent. This method recognizes and extracts only one person (user) directly facing the camera in a moving image in which several people occasionally enter and leave. The recognition method can be executed in real time in a typical indoor environment. The background and the lighting do not have to be restricted and recognition can be achieved in real time by a parallel computer. In addition, this technique simulates the initial stage of human visual functions and is based on the parallel extraction and integration of multiple image features. The movements of visual attention of cognitive psychology can also be simulated. An anthropomorphic agent derived from this approach successively looks at multiple human faces, fixes its gaze only on a specific person, and synthesizes agent behavior that approximate that of humans. These moving image recognition and synthesis processes were implemented on a newly designed parallel computer.
Shape, surface reflectance, illuminant direction and illuminant intensity from images with shading
Authors: Hayakawa Hideki 
Published: July 2007

AbstractA method is proposed for estimating shape, surface reflectance, illuminant direction and illuminant intensity from images with shading. First, ann x mimage data matrixIis constructed fromnpixel image inten‐sity data throughmframes by moving a light source arbitrarily. Using the Lambertian assumption, the image data matrixIcan be written as the product of two matricesNandS; Nrepresents the surface normal and surface reflectance, andSrepresents the illuminant direction and illuminant intensity. Based on this for‐mulation, a singular value decomposition technique is employed and one of the following two constraints is used to factorize the image data matrix.One is the constraint of surface reflectance which can be used when there are at least 6 pixels in the images, where the surface reflectance is constant. The other is the constraint of illuminant intensity which can be used when there are at least 6 frames among the images, where the illuminant intensity is constant.As the number of images with shading increases, the estimation errors become smaller even if the images are taken in a noisy environment. The proposed method can also treat self shadows and cast shadows without assumptions. The effectiveness of the proposed method is demonstrated through computer simulation, performance analysis and laboratory experiment.
High‐speed match algorithm of a production system
Authors: Kimura Haruhiko , Kobayashi Shin‐Ya , Takebe Tsuyoshi , Sumiyoshi Kazuyuki 
Published: July 2007

AbstractThe production system is suited to representing the miscellaneous pieces of human knowledge, and is used most widely in constructing the expert system. A problem is that a tremendous amount of time is required for the condition match, and an efficient condition match algorithm is desired.This paper considers the expert system which has been designed for the inference based on the semantic network, and aims at the realization of the high‐speed condition match in the expert system rewritten by OPS5. The working memory elements which are the objects of investigation are mostly the knowledge of two‐term relations, and the number of attributes usually is 2.This paper also proposes a data structure for the working memory, which can derive directly all working memory elements satisfying the condition, from the condition elements with 2 or less attributes. Using the proposed data structure, an algorithm is shown that can realize a high‐speed condition match. It is shown for the considered expert system that the proposed algorithm can realize a higher speed than the conventional condition match algorithm.
A multimodule neural network model and the estimate of its nature as associative memory
Authors: Ozawa Seichi , Tsutsumi Kazuyoshi 
Published: July 2007

AbstractA modular neural network model, “Cross‐Coupled Hopfield Nets with Many‐to‐Many Mapping Internetworks (CCHN‐MMMI),” in which the total consumed energy is defined as a linear sum of energy functions for subnetworks and their interactions, is proposed herein. This model can be applied to cases in which many‐to‐many mappings are necessary to mutually relate states of modules. The network dynamics are derived first, and then through computer simulations, the characteristics of the 2‐module CCHN‐MMMI are studied as associative memory. In one simulation, the effects of the introduction of explicitly modular architecture and a comparison of the results to those produced by conventional autocorrelation associative memory models.Another simulation shows that the model can store and recall pairs of character patterns successfully even if many‐to‐many mapping relations are necessary to relate the pairs to each other. A quantitative investigation as to how the recall dynamics deteriorate with an increasing number of randomly chosen fundamental memories is made in order to access the model as associative. The results indicate that internetworks between modules function effectively to prevent the entire network from recalling spurious memories. When multilayered networks with nonlinear hidden units are employed as internetworks in the model, the association performance is even more greatly improved as compared with conventional autocorrelation associative memory model.
A study of network logic for wafer‐scale parallel‐access memory and a yield analysis
Authors: Yamashita Koichi , Ikehara Shohei 
Published: July 2007

AbstractThe paper describes wafer‐scale memory design with network logic based on switching register circuit (SW‐REG), and defect tolerance schemes. Such a wafer‐scale memory is an array of chips, each consisting of a memory core and SW‐REG. The SW‐REG links neighboring chips of the same column, and each column is independently accessible from the outside. Monte Carlo simulation demonstrated that addition of driver transistors and spare lines to common signals, and bypass lines to SW‐REG are optimum defect tolerance schemes. When using 64 Mbit DRAM memory core on an 8‐inch wafer, wafer‐scale memory gives higher memory capacity than corresponding discrete chip system: for 5 percent memory core yield, 13 times higher memory capacity is achieved.
Multiple fault diagnosis in combinational circuits using sensitizing input‐pairs
Authors: Yanagida Nobuhiro , Takahashi Hiroshi , Takamatsu Yuzo 
Published: July 2007

AbstractThis paper presents a new method for multiple fault diagnosis of combinational circuits using sensitizing input‐pairs. A partition of a circuit under test into subtree circuits and a generation method for diagnostic test are described. The set of diagnostic tests used in this paper is one of sensitizing input‐pairs that generate sensitizing paths including checkpoints on them.By studying the relation between a sensitizing path generated by a sensitizing input‐pair and a subtree circuit, a method is presented for multiple fault diagnosis in the subtree circuit based on the fault‐free and the faulty responses observed at primary outputs. A deduction algorithm is described for a value at an output of a subtree circuit which does not have a primary output. The proposed method is applied to benchmark circuits having double faults, triple faults, and fourfold faults. Experimental results show that suspected faults are identified within 8 to 30 percent of all stuck‐at 0 and 1 faults on all lines in the circuit.