An Accurate Scene Segmentation Method Based on Graph Analysis Using Object Matching and Audio Feature

Makoto YAMAMOTO; Miki HASEYAMA

doi:10.1587/transfun.E92.A.1883

An Accurate Scene Segmentation Method Based on Graph Analysis Using Object Matching and Audio Feature

Makoto YAMAMOTO, Miki HASEYAMA

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A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E92-A No.8 pp.1883-1891

Publication Date: 2009/08/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E92.A.1883

Type of Manuscript: Special Section PAPER (Special Section on Signal Processing)

Category: Speech/Audio

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Makoto YAMAMOTO, Miki HASEYAMA, "An Accurate Scene Segmentation Method Based on Graph Analysis Using Object Matching and Audio Feature" in IEICE TRANSACTIONS on Fundamentals, vol. E92-A, no. 8, pp. 1883-1891, August 2009, doi: 10.1587/transfun.E92.A.1883.
Abstract: A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.1883/_p

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@ARTICLE{e92-a_8_1883,
author={Makoto YAMAMOTO, Miki HASEYAMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An Accurate Scene Segmentation Method Based on Graph Analysis Using Object Matching and Audio Feature},
year={2009},
volume={E92-A},
number={8},
pages={1883-1891},
abstract={A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.},
keywords={},
doi={10.1587/transfun.E92.A.1883},
ISSN={1745-1337},
month={August},}

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TY - JOUR
TI - An Accurate Scene Segmentation Method Based on Graph Analysis Using Object Matching and Audio Feature
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1883
EP - 1891
AU - Makoto YAMAMOTO
AU - Miki HASEYAMA
PY - 2009
DO - 10.1587/transfun.E92.A.1883
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2009
AB - A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.
ER -