Generating Semantic Annotation of Video for Organizing and Searching Traffic Resources

Zheng Xu, Fenglin Zhi, Chen Liang, Lin Mei and Xiangfeng Luo
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Zheng Xu: The Third Research Institute of Ministry of Public Security, Shanghai, China
Fenglin Zhi: The Third Research Institute of Ministry of Public Security, Shanghai, China
Chen Liang: The Third Research Institute of Ministry of Public Security, Shanghai, China
Lin Mei: The Third Research Institute of Ministry of Public Security, Shanghai, China
Xiangfeng Luo: Shanghai University, Shanghai, China

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2014, vol. 8, issue 1, 51-66

Abstract: Image and video resources play an important role in traffic events analysis. With the rapid growth of the video surveillance devices, large number of image and video resources is increasing being created. It is crucial to explore, share, reuse, and link these multimedia resources for better organizing traffic events. Most of the video resources are currently annotated in an isolated way, which means that they lack semantic connections. Thus, providing the facilities for annotating these video resources is highly demanded. These facilities create the semantic connections among video resources and allow their metadata to be understood globally. Adopting semantic technologies, this paper introduces a video annotation platform. The platform enables user to semantically annotate video resources using vocabularies defined by traffic events ontologies. Moreover, the platform provides the search interface of annotated video resources. The result of initial development demonstrates the benefits of applying semantic technologies in the aspects of reusability, scalability and extensibility.

Date: 2014
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