Towards intelligent photo composition-automatic detection of unintentional dissection lines in environmental portrait photos

C. T. Shen; J. C. Liu; S. W. Shih; J. S. Hong

doi:10.1016/j.eswa.2008.12.041

Towards intelligent photo composition-automatic detection of unintentional dissection lines in environmental portrait photos

C. T. Shen, J. C. Liu, S. W. Shih, J. S. Hong

Center for General Education

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

Good photos result from careful attention to various elements such as shutter speed, aperture, light exposure and composition. Over the years, there have been interests to develop digital still cameras with "composition advising" functions. However, not many composition-related functions have been realized in current digital cameras. This study proposed an approach for automatic detection of unintentional dissection lines which often degrade the aesthetics of an environmental portrait photo. The algorithm includes modules for face detection, ROI estimation, morphology filtering, edge detection and straight line detection. Experimental evaluations conducted to verify the performance of the algorithm show that the detection rate and false detection rate of general dissection lines are 80.87% and 33.61%, respectively.

Original language	English
Pages (from-to)	9024-9030
Number of pages	7
Journal	Expert Systems with Applications
Volume	36
Issue number	5
DOIs	https://doi.org/10.1016/j.eswa.2008.12.041
Publication status	Published - Jul 2009

Keywords

Aesthetic computing
Portrait composition
Unintentional dissection lines

ASJC Scopus subject areas

General Engineering
Computer Science Applications
Artificial Intelligence

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10.1016/j.eswa.2008.12.041

Cite this

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title = "Towards intelligent photo composition-automatic detection of unintentional dissection lines in environmental portrait photos",

abstract = "Good photos result from careful attention to various elements such as shutter speed, aperture, light exposure and composition. Over the years, there have been interests to develop digital still cameras with {"}composition advising{"} functions. However, not many composition-related functions have been realized in current digital cameras. This study proposed an approach for automatic detection of unintentional dissection lines which often degrade the aesthetics of an environmental portrait photo. The algorithm includes modules for face detection, ROI estimation, morphology filtering, edge detection and straight line detection. Experimental evaluations conducted to verify the performance of the algorithm show that the detection rate and false detection rate of general dissection lines are 80.87% and 33.61%, respectively.",

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T1 - Towards intelligent photo composition-automatic detection of unintentional dissection lines in environmental portrait photos

AU - Shen, C. T.

AU - Liu, J. C.

AU - Shih, S. W.

AU - Hong, J. S.

PY - 2009/7

Y1 - 2009/7

N2 - Good photos result from careful attention to various elements such as shutter speed, aperture, light exposure and composition. Over the years, there have been interests to develop digital still cameras with "composition advising" functions. However, not many composition-related functions have been realized in current digital cameras. This study proposed an approach for automatic detection of unintentional dissection lines which often degrade the aesthetics of an environmental portrait photo. The algorithm includes modules for face detection, ROI estimation, morphology filtering, edge detection and straight line detection. Experimental evaluations conducted to verify the performance of the algorithm show that the detection rate and false detection rate of general dissection lines are 80.87% and 33.61%, respectively.

AB - Good photos result from careful attention to various elements such as shutter speed, aperture, light exposure and composition. Over the years, there have been interests to develop digital still cameras with "composition advising" functions. However, not many composition-related functions have been realized in current digital cameras. This study proposed an approach for automatic detection of unintentional dissection lines which often degrade the aesthetics of an environmental portrait photo. The algorithm includes modules for face detection, ROI estimation, morphology filtering, edge detection and straight line detection. Experimental evaluations conducted to verify the performance of the algorithm show that the detection rate and false detection rate of general dissection lines are 80.87% and 33.61%, respectively.

KW - Aesthetic computing

KW - Portrait composition

KW - Unintentional dissection lines

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Towards intelligent photo composition-automatic detection of unintentional dissection lines in environmental portrait photos

Abstract

Keywords

ASJC Scopus subject areas

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