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Multi-modal Video Retrieval in Virtual Reality with vitrivr-VR

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MultiMedia Modeling (MMM 2022)

Abstract

In multimedia search, appropriate user interfaces (UIs) are essential to enable effective specification of the user’s information needs and the user-friendly presentation of search results. vitrivr-VR addresses these challenges and provides a novel Virtual Reality-based UI on top of the multimedia retrieval system vitrivr. In this paper we present the version of vitrivr-VR participating in the Video Browser Showdown (VBS) 2022. We describe our visual-text co-embedding feature and new query interfaces, namely text entry, pose queries and temporal queries.

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Notes

  1. 1.

    https://www.vitrivr.org/.

  2. 2.

    https://unity.com/.

  3. 3.

    https://docs.unity3d.com/Packages/com.unity.xr.openxr@latest.

  4. 4.

    https://keras.io/api/applications/inceptionresnetv2.

  5. 5.

    https://tfhub.dev/google/universal-sentence-encoder/4.

  6. 6.

    https://github.com/mozilla/DeepSpeech.

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Acknowledgements

This work was partly supported by the Swiss National Science Foundation (project “Participatory Knowledge Practices in Analog and Digital Image Archives”, contract no. CRSII5_193788).

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Correspondence to Florian Spiess .

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Spiess, F. et al. (2022). Multi-modal Video Retrieval in Virtual Reality with vitrivr-VR. In: Þór Jónsson, B., et al. MultiMedia Modeling. MMM 2022. Lecture Notes in Computer Science, vol 13142. Springer, Cham. https://doi.org/10.1007/978-3-030-98355-0_45

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  • DOI: https://doi.org/10.1007/978-3-030-98355-0_45

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