Evaluating Keyframe Layouts for Visual Known-Item Search in Homogeneous Collections
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914076355985408 |
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| author | Jäckl, Bastian Kruchina, Jiří Joos, Lucas Keim, Daniel A. Peška, Ladislav Lokoč, Jakub |
| author_facet | Jäckl, Bastian Kruchina, Jiří Joos, Lucas Keim, Daniel A. Peška, Ladislav Lokoč, Jakub |
| contents | Multimodal deep-learning models power interactive video retrieval by ranking keyframes in response to textual queries. Despite these advances, users must still browse ranked candidates manually to locate a target. Keyframe arrangement within the search grid highly affects browsing effectiveness and user efficiency, yet remains underexplored. We report a study with 49 participants evaluating seven keyframe layouts for the Visual Known-Item Search task. Beyond efficiency and accuracy, we relate browsing phenomena, such as overlooks, to layout characteristics. Our results show that a video-grouped layout is the most efficient, while a four-column, rank-preserving grid achieves the highest accuracy. Sorted grids reveal potentials and trade-offs, enabling rapid scanning of uninteresting regions but down-ranking relevant targets to less prominent positions, delaying first arrival times and increasing overlooks.
These findings motivate hybrid designs that preserve positions of top-ranked items while sorting or grouping the remainder, and offer guidance for searching in grids beyond video retrieval. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_04396 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evaluating Keyframe Layouts for Visual Known-Item Search in Homogeneous Collections Jäckl, Bastian Kruchina, Jiří Joos, Lucas Keim, Daniel A. Peška, Ladislav Lokoč, Jakub Multimedia Information Retrieval H.3.3; H.5.2; H.5.1 Multimodal deep-learning models power interactive video retrieval by ranking keyframes in response to textual queries. Despite these advances, users must still browse ranked candidates manually to locate a target. Keyframe arrangement within the search grid highly affects browsing effectiveness and user efficiency, yet remains underexplored. We report a study with 49 participants evaluating seven keyframe layouts for the Visual Known-Item Search task. Beyond efficiency and accuracy, we relate browsing phenomena, such as overlooks, to layout characteristics. Our results show that a video-grouped layout is the most efficient, while a four-column, rank-preserving grid achieves the highest accuracy. Sorted grids reveal potentials and trade-offs, enabling rapid scanning of uninteresting regions but down-ranking relevant targets to less prominent positions, delaying first arrival times and increasing overlooks. These findings motivate hybrid designs that preserve positions of top-ranked items while sorting or grouping the remainder, and offer guidance for searching in grids beyond video retrieval. |
| title | Evaluating Keyframe Layouts for Visual Known-Item Search in Homogeneous Collections |
| topic | Multimedia Information Retrieval H.3.3; H.5.2; H.5.1 |
| url | https://arxiv.org/abs/2510.04396 |