Video Summarise 入门
- Definition
- [Achieve method](#Achieve method)
- [What can chatgpt do for Video Summarise?](#What can chatgpt do for Video Summarise?)
- Literatures
Definition
"Video summarization" refers to the process of creating a concise and condensed representation of a video, capturing its essential content, key events, or highlights. The goal is to provide a shorter version of the video that retains its most important information, making it more accessible for viewers and easier to comprehend.
Achieve method
Video summarization can be achieved using various techniques, including:
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Keyframe Extraction: Selecting representative frames from the video to create a summary.
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Shot Boundary Detection: Identifying transitions between shots to divide the video into segments.
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Object or Activity Recognition: Using computer vision algorithms to recognize and highlight important objects or activities in the video.
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Temporal Sub-sampling: Selecting specific segments of the video to include in the summary while maintaining the temporal flow.
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Clustering and Classification: Grouping similar frames or shots together and selecting representative clusters.
The aim is to create a condensed version that captures the essence of the video, making it more manageable for users to review or comprehend the content without watching the entire video.
What can chatgpt do for Video Summarise?
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Textual Summaries: You can provide a description or transcript of the video to ChatGPT, and it can generate a concise summary based on the input.
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Clarification: If there are specific points in the video that need clarification or more context, you can ask ChatGPT for additional information.
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Question-Answering: If you have questions about specific details in the video, you can ask ChatGPT for answers, helping you understand and summarize the content.
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Scripting Assistance: If you're creating a script for a video summary, ChatGPT can help generate or refine the script based on your input.
Literatures
Title | Year | Publication |
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Video Summarise Using Deep Neural Networks: A surey | 2021 | IEEE |