Image rendering from the depth layer of a scene

In this exciting and challenging project, we have explored new possibilities of applying artistic rules into a landscape photograph by considering a depth-based partition as one of the input. Compared with other depth rendering techniques, our project not only can enhance the perception of depth, bu...

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Bibliographic Details
Main Author: Dang, Kang
Other Authors: Chan Kap Luk
Format: Final Year Project (FYP)
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/45225
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author Dang, Kang
author2 Chan Kap Luk
author_facet Chan Kap Luk
Dang, Kang
author_sort Dang, Kang
collection NTU
description In this exciting and challenging project, we have explored new possibilities of applying artistic rules into a landscape photograph by considering a depth-based partition as one of the input. Compared with other depth rendering techniques, our project not only can enhance the perception of depth, but also take artistic elements into consideration such as emphasizing the overall structuring and layout of images. Our project takes a template-based approach. User selects a photograph, gives the depth-based partition and selects a painting whose style would be used as a template. Rendering algorithms will generate an output image based these inputs and artistic rule. It is easy to identify three key issues: (1) partitioning of image according to its depth (2) extraction of rendering rules from the artistic principles (3) development of rendering algorithms for transferring the style of paintings to photos. These three issues have been thoroughly discussed in this report. In addition, a Graphics User Interface has been programmed to guide the user through the entire procedure and implementation is also mentioned in the report.
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spelling ntu-10356/452252023-07-07T15:47:15Z Image rendering from the depth layer of a scene Dang, Kang Chan Kap Luk School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision In this exciting and challenging project, we have explored new possibilities of applying artistic rules into a landscape photograph by considering a depth-based partition as one of the input. Compared with other depth rendering techniques, our project not only can enhance the perception of depth, but also take artistic elements into consideration such as emphasizing the overall structuring and layout of images. Our project takes a template-based approach. User selects a photograph, gives the depth-based partition and selects a painting whose style would be used as a template. Rendering algorithms will generate an output image based these inputs and artistic rule. It is easy to identify three key issues: (1) partitioning of image according to its depth (2) extraction of rendering rules from the artistic principles (3) development of rendering algorithms for transferring the style of paintings to photos. These three issues have been thoroughly discussed in this report. In addition, a Graphics User Interface has been programmed to guide the user through the entire procedure and implementation is also mentioned in the report. Bachelor of Engineering 2011-06-10T03:14:44Z 2011-06-10T03:14:44Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/45225 en Nanyang Technological University 66 p. application/pdf
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Dang, Kang
Image rendering from the depth layer of a scene
title Image rendering from the depth layer of a scene
title_full Image rendering from the depth layer of a scene
title_fullStr Image rendering from the depth layer of a scene
title_full_unstemmed Image rendering from the depth layer of a scene
title_short Image rendering from the depth layer of a scene
title_sort image rendering from the depth layer of a scene
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
url http://hdl.handle.net/10356/45225
work_keys_str_mv AT dangkang imagerenderingfromthedepthlayerofascene