Content-Based Video Indexing and Retrieval-- A Natural Language Approach--

Yeun-Bae KIM; Masahiro SHIBATA

Content-Based Video Indexing and Retrieval-- A Natural Language Approach--

Yeun-Bae KIM, Masahiro SHIBATA

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This paper describes methods in which natural language is used to describe video contents, knowledge of which is needed for intelligent video manipulation. The content encoded by natural language is extracted by a language analyzer in the form of subject-centered dependency structures which is a language-oriented structure, and is combined in an incremental way into a single structure called a multi-path index tree. Content descriptors and their inter-relations are extracted from the index tree in order to provide a high speed retrieval and flexibility. The content-based video index is represented in a two-dimensional structure where in the descriptors are mapped onto a component axis and temporal references (i.e., video segments aligned to the descriptors) are mapped onto a time axis. We implemented an experimental image retrieval systems to illustrate the proposed index structure 1) has superior retrieval capabilities compare to those used in conventional methods, 2) can be generated by an automated procedure, and 3) has a compact and flexible structure that is easily expandable, making an integration with vision processing possible.

Publication: IEICE TRANSACTIONS on Information Vol.E79-D No.6 pp.695-705

Publication Date: 1996/06/25

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Type of Manuscript: Special Section PAPER (Special Issue on Multimedia Computing and Communications)

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Yeun-Bae KIM, Masahiro SHIBATA, "Content-Based Video Indexing and Retrieval-- A Natural Language Approach--" in IEICE TRANSACTIONS on Information, vol. E79-D, no. 6, pp. 695-705, June 1996, doi: .
Abstract: This paper describes methods in which natural language is used to describe video contents, knowledge of which is needed for intelligent video manipulation. The content encoded by natural language is extracted by a language analyzer in the form of subject-centered dependency structures which is a language-oriented structure, and is combined in an incremental way into a single structure called a multi-path index tree. Content descriptors and their inter-relations are extracted from the index tree in order to provide a high speed retrieval and flexibility. The content-based video index is represented in a two-dimensional structure where in the descriptors are mapped onto a component axis and temporal references (i.e., video segments aligned to the descriptors) are mapped onto a time axis. We implemented an experimental image retrieval systems to illustrate the proposed index structure 1) has superior retrieval capabilities compare to those used in conventional methods, 2) can be generated by an automated procedure, and 3) has a compact and flexible structure that is easily expandable, making an integration with vision processing possible.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_6_695/_p

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@ARTICLE{e79-d_6_695,
author={Yeun-Bae KIM, Masahiro SHIBATA, },
journal={IEICE TRANSACTIONS on Information},
title={Content-Based Video Indexing and Retrieval-- A Natural Language Approach--},
year={1996},
volume={E79-D},
number={6},
pages={695-705},
abstract={This paper describes methods in which natural language is used to describe video contents, knowledge of which is needed for intelligent video manipulation. The content encoded by natural language is extracted by a language analyzer in the form of subject-centered dependency structures which is a language-oriented structure, and is combined in an incremental way into a single structure called a multi-path index tree. Content descriptors and their inter-relations are extracted from the index tree in order to provide a high speed retrieval and flexibility. The content-based video index is represented in a two-dimensional structure where in the descriptors are mapped onto a component axis and temporal references (i.e., video segments aligned to the descriptors) are mapped onto a time axis. We implemented an experimental image retrieval systems to illustrate the proposed index structure 1) has superior retrieval capabilities compare to those used in conventional methods, 2) can be generated by an automated procedure, and 3) has a compact and flexible structure that is easily expandable, making an integration with vision processing possible.},
keywords={},
doi={},
ISSN={},
month={June},}

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TY - JOUR
TI - Content-Based Video Indexing and Retrieval-- A Natural Language Approach--
T2 - IEICE TRANSACTIONS on Information
SP - 695
EP - 705
AU - Yeun-Bae KIM
AU - Masahiro SHIBATA
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 1996
AB - This paper describes methods in which natural language is used to describe video contents, knowledge of which is needed for intelligent video manipulation. The content encoded by natural language is extracted by a language analyzer in the form of subject-centered dependency structures which is a language-oriented structure, and is combined in an incremental way into a single structure called a multi-path index tree. Content descriptors and their inter-relations are extracted from the index tree in order to provide a high speed retrieval and flexibility. The content-based video index is represented in a two-dimensional structure where in the descriptors are mapped onto a component axis and temporal references (i.e., video segments aligned to the descriptors) are mapped onto a time axis. We implemented an experimental image retrieval systems to illustrate the proposed index structure 1) has superior retrieval capabilities compare to those used in conventional methods, 2) can be generated by an automated procedure, and 3) has a compact and flexible structure that is easily expandable, making an integration with vision processing possible.
ER -