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Various avatar animation techniques, ranging from full-body motion capture to single-point inverse kinematics (IK), offer different levels of realism. While the animation of a user\u2019s own avatar influences embodiment, the perceived realism of others\u2019 avatars is equally important for immersion. This study (\n                    <jats:italic>N<\/jats:italic>\n                    = 53) examines how users in smartphone AR, head-mounted display (HMD) AR, and VR perceive the behavioral realism of avatars animated with single-point IK compared to those driven by full-body motion capture. In addition, we explore whether the congruence between visual fidelity of an avatar and tracking accuracy affects perception. Our findings indicate that full-body motion capture produces significantly higher perceived realism than single-point IK, but the type of device does not have measurable impact. Furthermore, while congruence between visual realism and tracking fidelity was expected to play a role, our results suggest that its influence is limited. Despite lower realism than motion capture, modern IK techniques are still perceived positively, highlighting their viability for multi-user AR and VR applications.\n                  <\/jats:p>","DOI":"10.1007\/s00371-025-03934-5","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T06:22:49Z","timestamp":1748845369000},"page":"11721-11733","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evaluating behavioral realism in AR and VR: a comparison of single-point IK and full-body motion capture virtual humans"],"prefix":"10.1007","volume":"41","author":[{"given":"Elhassan","family":"Makled","sequence":"first","affiliation":[]},{"given":"Christoph","family":"Gerhardt","sequence":"additional","affiliation":[]},{"given":"Tobias","family":"Schwandt","sequence":"additional","affiliation":[]},{"given":"Florian","family":"Weidner","sequence":"additional","affiliation":[]},{"given":"Wolfgang","family":"Broll","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,2]]},"reference":[{"key":"3934_CR1","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445582","author":"K Ahuja","year":"2021","unstructured":"Ahuja, K., Mayer, S., Goel, M., Harrison, C.: Pose-on-the-go: approximating user pose with smartphone sensor fusion and inverse kinematics. 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