Interactive maps for a digital video library

Christel, Michael G.; Olligschlaeger, Andreas; Huang, Chang

doi:10.1109/93.839312

Cited by 47 publications

(27 citation statements)

References 6 publications

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“…One can quickly find the news video clips according to place names, highlight the place in the text and map when video was played. Because of the geographic information, one can quickly query news videos (Christel, Olligschlaeger, & Huang, 2000). Xiaotao Liu designed and implemented the automatic video annotation and querying system, named SEVA, with rich sensor information.…”

Section: Video Retrieval Methods Based On Geographic Informationmentioning

confidence: 99%

Geographic Video 3d Data Model And Retrieval

Han

Cui

Kong

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VI, WG VI/4KEY WORDS: Geographic Video, Data Model, 3D, GIS, Data Retrieval ABSTRACT:Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

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Section: Video Retrieval Methods Based On Geographic Informationmentioning

confidence: 99%

Geographic Video 3d Data Model And Retrieval

Han

Cui

Kong

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…As part of the Carnegie Mellon University's Informedia project, Christel et al proposed a news video browsing interface that visualizes news stories based on the combinations of the 3Ws focusing especially on the "Where" attribute [24], [25]. We focused on the cooccurrence of the "Who" attribute, and proposed a news video browsing interface by exploring the social network in news contents [26].…”

Section: Work On the Visualization Of News Structurementioning

confidence: 99%

Efficient Tracking of News Topics Based on Chronological Semantic Structures in a Large-Scale News Video Archive

Ide

Kinoshita²,

Takahashi

et al. 2012

IEICE Trans. Inf. & Syst.

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“…However, there has been very limited research on this problem [1,3,6]. The goal of this paper is to automatically annotate the location of every shot in broadcast news video.…”

Section: Introductionmentioning

confidence: 99%

“…A separate track of research has used GPS information to determine location [6], which is not available for news video. Christel et al [3] have successfully used locations extracted from the transcript of news video to create an map-based interface for browsing, but they did not correlate the locations with specific shots. To our knowledge, there is no working approach for annotating the locations of news video shots.…”

Section: Introductionmentioning

confidence: 99%

Annotating News Video with Locations

Yang

Hauptmann

2006

Lecture Notes in Computer Science

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Abstract. The location of video scenes is an important semantic descriptor especially for broadcast news video. In this paper, we propose a learning-based approach to annotate shots of news video with locations extracted from video transcript, based on features from multiple video modalities including syntactic structure of transcript sentences, speaker identity, temporal video structure, and so on. Machine learning algorithms are adopted to combine multi-modal features to solve two sub-problems: (1) whether the location of a video shot is mentioned in the transcript, and if so, (2) among many locations in the transcript, which are correct one(s) for this shot. Experiments on TRECVID dataset demonstrate that our approach achieves approximately 85% accuracy in correctly labeling the location of any shot in news video.

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Interactive maps for a digital video library

Cited by 47 publications

References 6 publications

Geographic Video 3d Data Model And Retrieval

Geographic Video 3d Data Model And Retrieval

Efficient Tracking of News Topics Based on Chronological Semantic Structures in a Large-Scale News Video Archive

Annotating News Video with Locations

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