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Current inside-out systems often rely on vision-based methods utilizing handheld controllers or incorporating densely distributed body-worn IMU sensors. The former limits hands-free and occlusion-robust interactions, while the latter is plagued by inadequate accuracy and jittering. We introduce a novel body tracking system, MI-Poser, which employs AR glasses and two wrist-worn electromagnetic field (EMF) sensors to achieve high-fidelity upper-body pose estimation while mitigating metal interference. Our lightweight system demonstrates a minimal error (6.6 cm mean joint position error) with real-world data collected from 10 participants. It remains robust against various upper-body movements and operates efficiently at 60 Hz. Furthermore, by incorporating an IMU sensor co-located with the EMF sensor, MI-Poser presents solutions to counteract the effects of metal interference, which inherently disrupts the EMF signal during tracking. Our evaluation effectively showcases the successful detection and correction of interference using our EMF-IMU fusion approach across environments with diverse metal profiles. Ultimately, MI-Poser offers a practical pose tracking system, particularly suited for body-centric AR applications.<\/jats:p>","DOI":"10.1145\/3610891","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T15:45:03Z","timestamp":1695829503000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["MI-Poser"],"prefix":"10.1145","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7868-4754","authenticated-orcid":false,"given":"Riku","family":"Arakawa","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0838-7858","authenticated-orcid":false,"given":"Bing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Snap Research, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1533-2169","authenticated-orcid":false,"given":"Gurunandan","family":"Krishnan","sequence":"additional","affiliation":[{"name":"Snap Research, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1237-7545","authenticated-orcid":false,"given":"Mayank","family":"Goel","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6452-6998","authenticated-orcid":false,"given":"Shree K.","family":"Nayar","sequence":"additional","affiliation":[{"name":"Snap Research, New York, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,9,27]]},"reference":[{"key":"e_1_2_2_1_1","volume-title":"Poppy Aves, Sang-Hoon Yeo, R Chris Miall, Peter Holland, and Joseph M Galea.","author":"Abdlkarim Diar","year":"2022","unstructured":"Diar Abdlkarim, Massimiliano Di Luca, Poppy Aves, Sang-Hoon Yeo, R Chris Miall, Peter Holland, and Joseph M Galea. 2022. 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