Single and multi-view 2D image processing for enhanced 3D object reconstruction

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliografiska uppgifter
Huvudupphovsmän:	Ghosh, Swapnil, Mahmud, Md. Muhtasim, Ahmed, Asrar, Turjo, Tashdid Al Shafi, Salim, Md. Shaeak Ibna
Övriga upphovsmän:	Alam, Md. Ashraful
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2024
Ämnen:	Convolutional neural network Depth camera Three-dimensional geometry Object reconstruction 3D object Computer vision. Image processing > Digital techniques. Optical pattern recognition. Three-dimensional imaging.
Länkar:	http://hdl.handle.net/10361/24361

id	10361-24361
record_format	dspace
spelling	10361-243612024-10-21T21:01:33Z Single and multi-view 2D image processing for enhanced 3D object reconstruction Ghosh, Swapnil Mahmud, Md. Muhtasim Ahmed, Asrar Turjo, Tashdid Al Shafi Salim, Md. Shaeak Ibna Alam, Md. Ashraful Department of Computer Science and Engineering, Brac University Convolutional neural network Depth camera Three-dimensional geometry Object reconstruction 3D object Computer vision. Image processing--Digital techniques. Optical pattern recognition. Three-dimensional imaging. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 57-60). This paper presents an efficient approach for 3D object reconstruction using Single and multi- view 2D image processing. In real-world scenarios, it also focuses on practical applications. Our approach is about the advanced image processing techniques as well as deep learning models which convert multiple 2D views of an object into a detailed 3D model. Our method is a novel application of convolutional neural networks that merge features from each view for ensuring consistent geometry and texture in the final model. Additionally, we introduce a robust merging module based on CNN. It improves the model’s fidelity by focusing on areas with significant detail variation across different views. Our tests on lots of challenging datasets show that our method enhances computational efficiency as well as it has significant potential for practical applications in areas such as virtual reality, augmented reality, and automated quality control in manufacturing. This research marks a significant step forward in digital imaging and computer vision, offering new possibilities for industry and technology advancements. Swapnil Ghosh Md. Muhtasim Mahmud Asrar Ahmed Tashdid Al Shafi Turjo Md. Shaeak Ibna Salim B.Sc. in Computer Science 2024-10-21T06:59:22Z 2024-10-21T06:59:22Z ©2024 2024-05 Thesis ID 20301470 ID 20101524 ID 20101522 ID 20101311 ID 20101044 http://hdl.handle.net/10361/24361 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 71 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Convolutional neural network Depth camera Three-dimensional geometry Object reconstruction 3D object Computer vision. Image processing--Digital techniques. Optical pattern recognition. Three-dimensional imaging.
spellingShingle	Convolutional neural network Depth camera Three-dimensional geometry Object reconstruction 3D object Computer vision. Image processing--Digital techniques. Optical pattern recognition. Three-dimensional imaging. Ghosh, Swapnil Mahmud, Md. Muhtasim Ahmed, Asrar Turjo, Tashdid Al Shafi Salim, Md. Shaeak Ibna Single and multi-view 2D image processing for enhanced 3D object reconstruction
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
author2	Alam, Md. Ashraful
author_facet	Alam, Md. Ashraful Ghosh, Swapnil Mahmud, Md. Muhtasim Ahmed, Asrar Turjo, Tashdid Al Shafi Salim, Md. Shaeak Ibna
format	Thesis
author	Ghosh, Swapnil Mahmud, Md. Muhtasim Ahmed, Asrar Turjo, Tashdid Al Shafi Salim, Md. Shaeak Ibna
author_sort	Ghosh, Swapnil
title	Single and multi-view 2D image processing for enhanced 3D object reconstruction
title_short	Single and multi-view 2D image processing for enhanced 3D object reconstruction
title_full	Single and multi-view 2D image processing for enhanced 3D object reconstruction
title_fullStr	Single and multi-view 2D image processing for enhanced 3D object reconstruction
title_full_unstemmed	Single and multi-view 2D image processing for enhanced 3D object reconstruction
title_sort	single and multi-view 2d image processing for enhanced 3d object reconstruction
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/24361
work_keys_str_mv	AT ghoshswapnil singleandmultiview2dimageprocessingforenhanced3dobjectreconstruction AT mahmudmdmuhtasim singleandmultiview2dimageprocessingforenhanced3dobjectreconstruction AT ahmedasrar singleandmultiview2dimageprocessingforenhanced3dobjectreconstruction AT turjotashdidalshafi singleandmultiview2dimageprocessingforenhanced3dobjectreconstruction AT salimmdshaeakibna singleandmultiview2dimageprocessingforenhanced3dobjectreconstruction
_version_	1814307595284905984

Single and multi-view 2D image processing for enhanced 3D object reconstruction

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