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- W2049763311 abstract "Museums are increasingly embracing technologies that provide highly-individualized and highly-interactive experiences to visitors. With embodied interaction experiences, increased localization accuracy supports greater nuance in interaction design, but there is usually a tradeoff between fast, accurate tracking and the ability to preserve the identity of users. Customization of experience relies on the ability to detect the identity of visitors, however. We present a method that combines fine-grained indoor tracking with robust preservation of the unique identities of multiple users. Our model merges input from an RFID reader with input from a commercial camera-based tracking system. We developed a probabilistic Bayesian model to infer at run-time the correct identification of the subjects in the camera's field of view. This method, tested in a lab and at a local museum, requires minimal modification to the exhibition space, while addressing several identity-preservation problems for which many indoor tracking systems do not have robust solutions." @default.
- W2049763311 created "2016-06-24" @default.
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- W2049763311 date "2013-04-27" @default.
- W2049763311 modified "2023-10-16" @default.
- W2049763311 title "I see you there!" @default.
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- W2049763311 doi "https://doi.org/10.1145/2470654.2466252" @default.
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