Giunchi, D;
Sztrajman, A;
James, S;
Steed, A;
(2021)
Mixing Modalities of 3D Sketching and Speech for Interactive Model Retrieval in Virtual Reality.
In:
Proceedings of the IMX 2021.
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
Sketch and speech are intuitive interaction methods that convey complementary information and have been independently used for 3D model retrieval in virtual environments. While sketch has been shown to be an effective retrieval method, not all collections are easily navigable using this modality alone. We design a new challenging database for sketch comprised of 3D chairs where each of the components (arms, legs, seat, back) are independently colored. To overcome this, we implement a multimodal interface for querying 3D model databases within a virtual environment. We base the sketch on the state-of-the-art for 3D Sketch Retrieval, and use a Wizard-of-Oz style experiment to process the voice input. In this way, we avoid the complexities of natural language processing which frequently requires fine-tuning to be robust. We conduct two user studies and show that hybrid search strategies emerge from the combination of interactions, fostering the advantages provided by both modalities.
Type: | Proceedings paper |
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Title: | Mixing Modalities of 3D Sketching and Speech for Interactive Model Retrieval in Virtual Reality |
Event: | IMX '21: ACM International Conference on Interactive Media Experiences 2021 |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://doi.org/10.1145/3452918.3458806 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10128756 |
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