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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Nanyang Technological University
2022
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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 |
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Engineering::Computer science and engineering Liu, Yanli From an image to a text description of the image |
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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. |
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Chng Eng Siong |
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Chng Eng Siong Liu, Yanli |
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Final Year Project |
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Liu, Yanli |
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Liu, Yanli |
title |
From an image to a text description of the image |
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From an image to a text description of the image |
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From an image to a text description of the image |
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From an image to a text description of the image |
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From an image to a text description of the image |
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from an image to a text description of the image |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/156521 |
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