Before Smelling the Video: A Two-Stage Pipeline for Interpretable Video-to-Scent Plans
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866915757609189376 |
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| author | Wang, Kaicheng Shao, Kevin Zhongyang Chen, Ruiqi Makhsous, Sep Wilson, Denise |
| author_facet | Wang, Kaicheng Shao, Kevin Zhongyang Chen, Ruiqi Makhsous, Sep Wilson, Denise |
| contents | Olfactory cues can enhance immersion in interactive media, yet smell remains rare because it is difficult to author and synchronize with dynamic video. Prior olfactory interfaces rely on designer triggers and fixed event-to-odor mappings that do not scale to unconstrained content. This work examines whether semantic planning for smell is intelligible to people before physical scent delivery. We present a video-to-scent planning pipeline that separates visual semantic extraction using a vision-language model from semantic-to-olfactory inference using a large language model. Two survey studies compare system-generated scent plans with over-inclusive and naive baselines. Results show consistent preference for plans that prioritize perceptually salient cues and align scent changes with visible actions, supporting semantic planning as a foundation for future olfactory media systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_19203 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Before Smelling the Video: A Two-Stage Pipeline for Interpretable Video-to-Scent Plans Wang, Kaicheng Shao, Kevin Zhongyang Chen, Ruiqi Makhsous, Sep Wilson, Denise Human-Computer Interaction H.5.2 Olfactory cues can enhance immersion in interactive media, yet smell remains rare because it is difficult to author and synchronize with dynamic video. Prior olfactory interfaces rely on designer triggers and fixed event-to-odor mappings that do not scale to unconstrained content. This work examines whether semantic planning for smell is intelligible to people before physical scent delivery. We present a video-to-scent planning pipeline that separates visual semantic extraction using a vision-language model from semantic-to-olfactory inference using a large language model. Two survey studies compare system-generated scent plans with over-inclusive and naive baselines. Results show consistent preference for plans that prioritize perceptually salient cues and align scent changes with visible actions, supporting semantic planning as a foundation for future olfactory media systems. |
| title | Before Smelling the Video: A Two-Stage Pipeline for Interpretable Video-to-Scent Plans |
| topic | Human-Computer Interaction H.5.2 |
| url | https://arxiv.org/abs/2601.19203 |