Searching for the shortest paths from a query point to several target points on a road network is an essential operation for several types of queries in location-based services. This search can be performed using Dijkstra's algorithm. Although the A* algorithm is faster than Dijkstra's algorithm for finding the shortest path from a query point to a target point, the A* algorithm is not so fast to find all paths between each point and the query point when several target points are given. In this case, the search areas on road network overlap for each search, and the total number of operations at each node is increased, especially when the number of query points increases. In the present paper, we propose the single-source multi-target A* (SSMTA*) algorithm, which is a multi-target version of the A* algorithm. The SSMTA* algorithm guarantees at most one operation for each road network node, and the searched area on road network is smaller than that of Dijkstra's algorithm. Deng et al. proposed the LBC approach with the same objective. However, several heaps are used to manage the search area on the road network and the contents in each heap must always be kept the same in their method. This operation requires much processing time. Since the proposed method uses only one heap, such content synchronization is not necessary. The present paper demonstrates through empirical evaluations that the proposed method outperforms other similar methods.

The present study describes using the state transition type of drawing understanding framework to construct a multi-purpose drawing understanding system. This new system employs an understanding process that complies with the understanding rules, which are easily obtained by the user. The same set of user-provided rules must be used for the same type of target drawings, but for slightly different ones, fine tuning is required to obtain understanding rules. To overcome this inherent drawback in constructing drawing understanding systems, we extended the system using a newly constructed understanding rule generating support system. The resultant integrated system is based on a man-machine cooperation type interface, and can automatically generate rules from user-provided simple interactions using a graphical user interace (GUI). To obtain efficient rule generation, the system employs an inductive inference method as a learning algorithm. Map-drawing experiments were successfully carried out, and an evaluation based on a rule leaning error criterion subsequently revealed an efficient rule generation process.

Among ITS applications, it is very important to acquire detailed statistics of traffic flows. For that purpose, vision sensors have an advantage because of their rich information compared to such spot sensors such as loop detectors or supersonic wave sensors. However, for many years, vehicle tracking in traffic images has suffered from the problems of occlusion effect and illumination effect. In order to resolve occlusion problems, we have been proposing the Spatio-Temporal Markov Random Field model(S-T MRF) for segmentation of Spatio-Temporal images. This S-T MRF model optimizes the segmentation boundaries of occluded vehicles and their motion vectors simultaneously by referring to textures and segment labeling correlations along the temporal axis as well as the spatial axis. Consequently, S-T MRF has been proven to be successful for vehicle tracking even against severe occlusions found in low-angle traffic images with complicated motions, such at highway junctions. In addition, in this paper, we define a method for obtaining illumination-invariant images by estimating MRF energy among neighbor pixel intensities. These illumination-invariant images are very stable even when sudden variations in illumination or shading effect are occurred in the original images. We then succeeded in seamlessly integrating the method for MRF energy images into our S-T MRF model. Thus, vehicle tracking was performed successfully by S-T MRF, even against sudden variations in illumination and against shading effects . Finally, in order to verify the effectiveness of our tracking algorithm based on the S-T MRF for practical uses, we developed an automated system for acquiring traffic statistics out of a flow of traffic images. This system has been operating continuously for ten months, and thus effectiveness of the tracking algorithm based on S-T MRF model was proven.

Multimedia Database Systems as the tool to extract and generate additional values from multimedia 'Contents' are discussed in this paper with putting emphasis on the mediator functions between users and contents. Firstly, we discuss about 'what to do' from the view point of four promising contents sources: 'on the network,' 'in the digital broadcasting' 'in the library' and 'in the real world.' From this view pont, four types of multimedia database systems are defined. 'What to do' for each database system is also discussed. Two concrete multimedia database systems with unique mediator functions, stream-type multimedia database platform GOLS and the intelligent access and authoring system using multiple media synchronization are proposed with experimental evaluation results and concrete multimedia database applications.

This letter presents a new method to efficiently extract closed loops as primitive symbols in line drawings. Our method uses a graph search technique for efficiency and exhaustibility, and also incorporates feasibility criteria of symbols. Experiments clearly demonstrated the method's effectiveness.

Recently, a flexible image database retrieval system where image keywords can be captured automatically is strongly required, in order to manage a practical number of image data successfully. However, image recognition/understanding technology level is not generally sufficient enough to achieve this requirement. In order to overcome this problem, a new type of image database framework is proposed in this paper. In the proposed system, image keywords are extracted in fully-automated fashion by the flexible and generalized image recognition system. Image keywords employed in this system are a collection of recognized objects in the image, where achieved recognition levels are allowed to be intermediate or imperfect. The concept of recognition thesaurus" has been introduced to manage these various abstraction level of kerwords successfully. As an embodiment of this concept, an experimental image database with various types of sports scenes has been implemented and various retrieval evaluations have been performed. Experimental results reveal the effectiveness of the proposed method.

A virtual city, a virtual reality system to display an urban scene, is one of the most promising tools for ITS applications, including car navigation aids, shopping guides, and city planning, to name a few. This paper overviews our effort to create virtual cities through a sequence of images obtained with vision/range sensors. Our virtual city consists not of only stationary buildings but also of running and parked vehicles, which reflect the current activities in the real city. The first part of this paper describes how to construct still building images from a sequence of images. Here, we focus on methods employing an omni image camera that acquires images containing rays of 360 degrees viewing directions. The second part describes a system to display vehicle movement in the virtual city based on the image sequence given with a monitoring TV camera at an intersection. It also describes a preliminary step toward displaying illegal parked vehicles from information collected by a probe car.