Publikation: CADTrack : Instructions and Support for Orientation Disambiguation of Near-Symmetrical Objects
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Determining the correct orientation of objects can be critical to succeed in tasks like assembly and quality assurance. In particular, near-symmetrical objects may require careful inspection of small visual features to disambiguate their orientation. We propose CADTrack, a digital assistant for providing instructions and support for tasks where the object orientation matters but may be hard to disambiguate with the naked eye. Additionally, we present a deep learning pipeline for tracking the orientation of near-symmetrical objects. In contrast to existing approaches, which require labeled datasets involving laborious data acquisition and annotation processes, CADTrack uses a digital model of the object to generate synthetic data and train a convolutional neural network. Furthermore, we extend the architecture of Mask R-CNN with a confidence prediction branch to avoid errors caused by misleading orientation guidance. We evaluate CADTrack in a user study, comparing our tracking-based instructions to other methods to confirm the benefits of our approach in terms of preference and required effort.
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EVANGELISTA BELO, João Marcelo, Jon WISSING, Tiare FEUCHTNER, Kaj GRØNBÆK, 2023. CADTrack : Instructions and Support for Orientation Disambiguation of Near-Symmetrical Objects. In: Proceedings of the ACM on Human-Computer Interaction. ACM. 2023, 7(ISS), 426. eISSN 2573-0142. Available under: doi: 10.1145/3626462BibTex
@article{EvangelistaBelo2023CADTr-68083, year={2023}, doi={10.1145/3626462}, title={CADTrack : Instructions and Support for Orientation Disambiguation of Near-Symmetrical Objects}, number={ISS}, volume={7}, journal={Proceedings of the ACM on Human-Computer Interaction}, author={Evangelista Belo, João Marcelo and Wissing, Jon and Feuchtner, Tiare and Grønbæk, Kaj}, note={Article Number: 426} }
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