From an image to a text description of the image

Information technology is changing rapidly, multimedia video with its rich information content, diverse presentation, convenient transmission, and storage form is rapidly replacing the traditional paper text. The amount of video data is growing in a spurt. In the face of the vast sea of news video,...

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Bibliographic Details
Main Author: Liu, Yanli
Other Authors: Chng Eng Siong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/156521
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1565212022-04-19T06:38:12Z From an image to a text description of the image Liu, Yanli Chng Eng Siong School of Computer Science and Engineering ASESChng@ntu.edu.sg Engineering::Computer science and engineering Information technology is changing rapidly, multimedia video with its rich information content, diverse presentation, convenient transmission, and storage form is rapidly replacing the traditional paper text. The amount of video data is growing in a spurt. In the face of the vast sea of news video, how to quickly and accurately retrieve and store video information has become a pressing problem. Video uses images and sound to convey information. To achieve this purpose, the visual summaries of broadcast news videos can first be recovered by extracting the video’s important frames, resulting in a collection of images that is a good representation of the video’s visual content. Image captioning is then used to assign relevant descriptions to the extracted keyframes. Meanwhile, the audio of the video is extracted to be processed. Not only the speech content itself but also the background sound indicate the news content. This project implements a fully automated video captioning system designed specifically for broadcast news video. To perform image captioning, the proposed system uses shot-based boundary detection to extract important frames, and a CLIP prefix + GTP2 model is used for image caption. The system’s accuracy is measured using the MS COCO dataset, and it’s compared to the current state-of-the-art in image captioning. Also presented is a method for evaluating the generated video captions against a set of annotated keyframes. Bachelor of Engineering (Computer Science) 2022-04-19T06:38:11Z 2022-04-19T06:38:11Z 2022 Final Year Project (FYP) Liu, Y. (2022). From an image to a text description of the image. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156521 https://hdl.handle.net/10356/156521 en SCSE21-0061 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Liu, Yanli
From an image to a text description of the image
description Information technology is changing rapidly, multimedia video with its rich information content, diverse presentation, convenient transmission, and storage form is rapidly replacing the traditional paper text. The amount of video data is growing in a spurt. In the face of the vast sea of news video, how to quickly and accurately retrieve and store video information has become a pressing problem. Video uses images and sound to convey information. To achieve this purpose, the visual summaries of broadcast news videos can first be recovered by extracting the video’s important frames, resulting in a collection of images that is a good representation of the video’s visual content. Image captioning is then used to assign relevant descriptions to the extracted keyframes. Meanwhile, the audio of the video is extracted to be processed. Not only the speech content itself but also the background sound indicate the news content. This project implements a fully automated video captioning system designed specifically for broadcast news video. To perform image captioning, the proposed system uses shot-based boundary detection to extract important frames, and a CLIP prefix + GTP2 model is used for image caption. The system’s accuracy is measured using the MS COCO dataset, and it’s compared to the current state-of-the-art in image captioning. Also presented is a method for evaluating the generated video captions against a set of annotated keyframes.
author2 Chng Eng Siong
author_facet Chng Eng Siong
Liu, Yanli
format Final Year Project
author Liu, Yanli
author_sort Liu, Yanli
title From an image to a text description of the image
title_short From an image to a text description of the image
title_full From an image to a text description of the image
title_fullStr From an image to a text description of the image
title_full_unstemmed From an image to a text description of the image
title_sort from an image to a text description of the image
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/156521
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