ExpressEdit: Video Editing with Natural Language and Sketching

Fuente: arXiv
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Hauptverfasser: Tilekbay, Bekzat, Yang, Saelyne, Lewkowicz, Michal, Suryapranata, Alex, Kim, Juho
Format: Preprint
Veröffentlicht: 2024
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author Tilekbay, Bekzat
Yang, Saelyne
Lewkowicz, Michal
Suryapranata, Alex
Kim, Juho
author_facet Tilekbay, Bekzat
Yang, Saelyne
Lewkowicz, Michal
Suryapranata, Alex
Kim, Juho
contents Informational videos serve as a crucial source for explaining conceptual and procedural knowledge to novices and experts alike. When producing informational videos, editors edit videos by overlaying text/images or trimming footage to enhance the video quality and make it more engaging. However, video editing can be difficult and time-consuming, especially for novice video editors who often struggle with expressing and implementing their editing ideas. To address this challenge, we first explored how multimodality$-$natural language (NL) and sketching, which are natural modalities humans use for expression$-$can be utilized to support video editors in expressing video editing ideas. We gathered 176 multimodal expressions of editing commands from 10 video editors, which revealed the patterns of use of NL and sketching in describing edit intents. Based on the findings, we present ExpressEdit, a system that enables editing videos via NL text and sketching on the video frame. Powered by LLM and vision models, the system interprets (1) temporal, (2) spatial, and (3) operational references in an NL command and spatial references from sketching. The system implements the interpreted edits, which then the user can iterate on. An observational study (N=10) showed that ExpressEdit enhanced the ability of novice video editors to express and implement their edit ideas. The system allowed participants to perform edits more efficiently and generate more ideas by generating edits based on user's multimodal edit commands and supporting iterations on the editing commands. This work offers insights into the design of future multimodal interfaces and AI-based pipelines for video editing.
format Preprint
id arxiv_https___arxiv_org_abs_2403_17693
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ExpressEdit: Video Editing with Natural Language and Sketching
Tilekbay, Bekzat
Yang, Saelyne
Lewkowicz, Michal
Suryapranata, Alex
Kim, Juho
Human-Computer Interaction
Artificial Intelligence
Informational videos serve as a crucial source for explaining conceptual and procedural knowledge to novices and experts alike. When producing informational videos, editors edit videos by overlaying text/images or trimming footage to enhance the video quality and make it more engaging. However, video editing can be difficult and time-consuming, especially for novice video editors who often struggle with expressing and implementing their editing ideas. To address this challenge, we first explored how multimodality$-$natural language (NL) and sketching, which are natural modalities humans use for expression$-$can be utilized to support video editors in expressing video editing ideas. We gathered 176 multimodal expressions of editing commands from 10 video editors, which revealed the patterns of use of NL and sketching in describing edit intents. Based on the findings, we present ExpressEdit, a system that enables editing videos via NL text and sketching on the video frame. Powered by LLM and vision models, the system interprets (1) temporal, (2) spatial, and (3) operational references in an NL command and spatial references from sketching. The system implements the interpreted edits, which then the user can iterate on. An observational study (N=10) showed that ExpressEdit enhanced the ability of novice video editors to express and implement their edit ideas. The system allowed participants to perform edits more efficiently and generate more ideas by generating edits based on user's multimodal edit commands and supporting iterations on the editing commands. This work offers insights into the design of future multimodal interfaces and AI-based pipelines for video editing.
title ExpressEdit: Video Editing with Natural Language and Sketching
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2403.17693