15731243
TORNADO: omnistereo video imaging with rotating optics
One of the key techniques for vision-based communication is omnidirectional stereo (omnistereo) imaging, in which stereoscopic images for an arbitrary horizontal direction are captured and presented according to the viewing direction of the observer. Although omnistereo models have been surveyed in several studies, few omnistereo sensors have actually been implemented. In this paper, a practical method for capturing omnistereo video sequences using rotating optics is proposed and evaluated. The rotating optics system consists of prism sheets, circular or linear polarizing films, and a hyperboloidal mirror. This system has two different modes of operation with regard to the separation of images for the left and right eyes. In the high-speed shutter mode, images are separated using postimage processing, while, in the low-speed shutter mode, the image separation is completed by optics. By capturing actual images, we confirmed the effectiveness of the methods.
18847598
A method for panoramic stereo image acquisition
One of the key technologies for one-to-many visual communication is panoramic stereo, in which stereoscopic images for arbitrary horizontal directions are presented to multiple users, according to their positions and postures. In this paper, one of the methods for capturing panoramic stereo motion pictures is proposed and evaluated, along with an experimentation. Through preliminary experimentation, we have confirmed the effectiveness of methods using a curved mirror.
5408151
Alternative Objects in Object-oriented Databases
26205197
Behavior Analysis of Object-Oriented Databases: Method Structure, Execution Trees, and Reachability (Extended Abstract)
A theoretical model for analyzing the behavior of method execution in object-oriented databases (OODBs) is introduced and used to study issues of reachability, nontermination, and well-typedness in the context of restricted classes of OODBs.
46574197
On Natural Joins in Object-Oriented Databases
In this paper, we introduce a recursively-defined natural join operation for composing complex objects. The notable features of our natural join are (1) Operand types are generalized into atomic-type, set-type, and tuple-type objects, and (2) The elements of set-type objects are allowed to be heterogenous. Then, we discuss how to realize the natural join by the message passing computing mechanism. Finally, we investigate some mathematical properties about the natural join. Especially, we provide a condition under which the sub-object relationship defined by Bancilhon and Khoshafian is preserved under our natural join and investigate the relationship between their intersection and our natural join.
3247078
Individual Level Analysis Using Decision Making Features in Multiagent Based Simulation
We introduce a set of evaluation tools in the framework of individual level analysis for multiagent based simulations. These tools are intended to overcome the weak points of multiagent systems: that it is difficult to avoid mistakes in description and arbitrary modeling; and to find reliable explanations of causal relationships between the model and its result. We analyze some artificial market models using an evaluation process that consists of the evaluation of initial learning maturity, discrimination between models, and the visualization of attention tendency in a group. We conclude that these analytical methods are useful for the evaluation of multiagent based simulations in terms of validation and finding causal relations.
7133208
Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model and maximum likelihood estimation. Although hyperparameters in the probabilistic model are determined so as to maximize a marginal likelihood, a practical algorithm is described for the EM algorithm with the loopy belief propagation which is one of approximate inference algorithms in artificial intelligence