You’ve gotten doubtless encountered presentation-style movies that mix slides, figures, tables, and spoken explanations. These movies have change into a broadly used medium of delivering data, significantly after the COVID-19 pandemic when stay-at-home measures have been carried out.
Whereas movies are an attractive technique to entry content material, a big downside is that they’re time-consuming, since one should watch your entire video to seek out particular data. In addition they take up appreciable cupboard space resulting from their massive file dimension.
Researchers led by Professor Hyuk-Yoon Kwon at Seoul Nationwide College of Science and Expertise in South Korea aimed to handle these points with PV2DOC, a software program device that converts presentation movies into summarized paperwork. Not like different video summarizers, which require a transcript alongside the video and change into ineffective when solely the video is out there, PV2DOC overcomes this limitation by combining each visible and audio information and changing video into paperwork.
Their analysis was made accessible on-line on October 11, 2024, and was printed within the journal SoftwareX on December 1, 2024.
“For customers who want to look at and research quite a few movies, equivalent to lectures or convention displays, PV2DOC generates summarized experiences that may be learn inside two minutes. Moreover, PV2DOC manages figures and tables individually, connecting them to the summarized content material so customers can seek advice from them when wanted,” explains Prof. Kwon.
For picture processing, PV2DOC extracts frames from the video at one-second intervals. It makes use of a way referred to as the structural similarity index, which compares every body with the earlier one to determine distinctive frames. Objects in every body, equivalent to figures, tables, graphs, and equations, are then detected by object detection fashions, Masks R-CNN and YOLOv5.
Throughout this course of, some photos might change into fragmented resulting from whitespace or sub-figures. To resolve this, PV2DOC makes use of a determine merge approach that identifies overlapping areas and combines them right into a single determine. Subsequent, the system applies optical character recognition (OCR) utilizing the Google Tesseract engine to extract textual content from the pictures. The extracted textual content is then organized right into a structured format, equivalent to headings and paragraphs.
Concurrently, PV2DOC extracts the audio from the video and makes use of the Whisper mannequin, an open-source speech-to-text (STT) device, to transform it into written textual content. The transcribed textual content is then summarized utilizing the TextRank algorithm, making a abstract of the details.
The extracted photos and textual content are mixed right into a Markdown doc, which will be changed into a PDF file. The ultimate doc presents the video’s content material—equivalent to textual content, figures, and formulation—in a transparent and arranged method, following the construction of the unique video.
By changing unorganized video information into structured, searchable paperwork, PV2DOC enhances the accessibility of the video and reduces the cupboard space wanted for sharing and storing the video.
“This software program simplifies information storage and facilitates information evaluation for presentation movies by remodeling unstructured information right into a structured format, thus providing important potential from the views of knowledge accessibility and information administration. It offers a basis for extra environment friendly utilization of presentation movies,” says Prof. Kwon.
The researchers plan to additional streamline video content material into accessible codecs. Their subsequent objective is to coach a big language mannequin (LLM), much like ChatGPT, to supply a question-answering service, the place customers can ask questions primarily based on the content material of the movies, with the mannequin producing correct, contextually related solutions.
Extra data:
Gained-Ryeol Jeong et al, PV2DOC: Changing the presentation video into the summarized doc, SoftwareX (2024). DOI: 10.1016/j.softx.2024.101922
Supplied by
Seoul Nationwide College of Science & Expertise
Quotation:
PV2DOC: New device summarizes presentation movies into searchable, structured PDF paperwork (2024, December 30)
retrieved 30 December 2024
from https://techxplore.com/information/2024-12-pv2doc-tool-videos-searchable-pdf.html
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