combined with depth and color measurements of the surrounding environment. Localization could be achieved with GPS, inertial measurement units (IMU), cameras, or combinations of these and other devices, while the depth measurements could be achieved with time-of-flight, radar or laser scanning systems. The resulting 3D maps, which are composed of 3D point clouds with various attributes, could be used for a variety of applications, including finding your way around indoor spaces, navigating vehicles around a city, space planning, topographical surveying or public surveying of infrastructure and roads, augmented reality, immersive online experiences, and much more. This paper discusses application requirements related to the representation and coding of large-scale 3D dynamic maps. In particular, we address requirements related to different types of acquisition environments, scalability in terms of progressive transmission and efficiently rendering different levels of details, as well as key attributes to be included in the representation. Additionally, an overview of recently developed coding techniques is presented, including an assessment of current performance. Finally, technical challenges and needs for future standardization are discussed.
In this paper, we present "PanoramaSeek", a new video streaming system suitable for Internet video retrieval. The system features intelligent streaming, which enables users to take quick glances at arbitrary portions of a video sequence by using slide bars. The streaming system utilizes multi-level interactive streaming and content-based selection of key frames. Multi-level interactive streaming supports three levels of display on a video window: key frame display, normal playback, and specific frame display. Users can switch between levels at any time. Content-based selection of key frames defines key frames by analyzing the changes occurring in video sequences and selecting appropriate, representative frames. Our evaluation of the system demonstrated that multi-level interactive streaming is effective in providing users with random browsing capability, and that content-based selection of key frames improves the efficiency of video retrieval by reducing the number of frames users have to check.
KEYWORDS: Automatic tracking, Video, Detection and tracking algorithms, Video compression, Databases, Human-machine interfaces, Data processing, Image processing, Systems modeling, Data modeling
Video hypermedia systems enable users to retrieve information related to an object by selecting it directly in a video sequence. In video hypermedia systems, users must locate an anchor position according to the motion of the object. But it is very laborious to locate an anchor to its suitable position according to the motion of the object. We have proposed a new automatic object tracking method and implemented it to the system. A feature of this method is that it includes various automatic error correction algorithms. We evaluated this system on effectiveness on reducing human operations. As a result, the number of operations reduced to 30.3% of the former method, and the time of operations reduced to 60.1% of the former method.
In this paper, a method of image information retrieval is presented. The method employs a new similarity measure between graph representations of images. The measure is effective for drawing images that describe logical meaning by their structure. Most of the currently available image database systems offer retrieval functions called key word retrieval, where users specify key words such as titles, attributes, and categories of themes. But it is not easy for the users to select suitable key words according to the purpose of retrieval. So recently some retrieval functions called similarity retrieval have been proposed, where users specify key images by means of examples, sketches, and icons. We are developing a drawing image database system that stores plant diagrams. The system scans, recognizes, and stores plant diagrams. Then users can refer to any parts of the diagrams according to their needs. The system is used as a help to plant observation and control. To realize similarity retrieval for logically structured drawings like plant diagrams, we introduced a graph representation of drawings, which is suitable to deal with their logical structure. Then we defined a similarity measure between them. In this paper, effectiveness of the similarity measure and applicability to plant diagrams are discussed and some experimental results are shown.
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