Abstract
We propose a video search system with a three-level hierarchy model for searching videos from works, scenes, and shots. Videos are useful research materials; however, their scholarly use is very limited because finding the desired information is a time-consuming task for scholars. To provide solutions to this problem, we developed a system with functions to increase search efficiency. This paper mentions the reasons preventing the scholarly use of videos and describes the methods used to develop the system, focusing on database creation and the prototype’s interface.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Note that this prototype is a closed caption based search system, not based on video recognition and open caption base.
References
Andreano, K.: The missing link: content indexing, user-created metadata, and improving scholarly access to moving image archives. Moving Image 7(2), 82–99 (2007)
Lu, C., Liu, M., Wu, Z.: SVQL: A SQL extended query language for video databases. Int. J. Database Theory Appl. 8(3), 235–248 (2015)
Li, Z.: An XML-based system for management and query of video databases with user identifiable and annotated scenes. Graduate theses and dissertations, Paper 14231 (2014)
Daga, B.S., Ghatol, A.A.: Detection of objects and activities in videos using spatial relations and ontology based approach in video database system. Int. J. Adv. Eng. Technol. 9(6), 640–650 (2016)
Nikam, P.: Nandwalkar, B.R: Fuzzy ontology and rule based model for automatic semantic content extraction from videos using k-means algorithm. Int. J. Comput. Appl. 130(13), 11–16 (2015)
Ganesh, K.R., Kanthavel, R., Celin, A.V.: Ontology and rule-based model for extracting semantic content in videos. J. Theoret. Appl. Inf. Technol. 62(2), 350–355 (2014)
Acknowledgement
This study was funded by the Chuo University Grant for Special Research. We are grateful to the members of our laboratory for their valuable insights, feedback, and much helpful support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Lee, T., Iio, J. (2018). ELVIDS: Video Search System Prototype with a Three-Level Hierarchy Model. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_101
Download citation
DOI: https://doi.org/10.1007/978-3-319-65521-5_101
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-65520-8
Online ISBN: 978-3-319-65521-5
eBook Packages: EngineeringEngineering (R0)