{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:14:53Z","timestamp":1758672893310,"version":"3.44.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:p>Managing novelty in perception-based human activity recognition (HAR) is critical in realistic settings to improve task performance over time and ensure solution generalization outside of prior seen samples. Novelty manifests in HAR as unseen samples, activities, objects, environments, and sensor changes, among other ways. Novelty may be task-relevant, such as a new class or new features, or task-irrelevant resulting in nuisance novelty, such as never before seen noise, blur, or distorted video recordings. To perform HAR optimally, algorithmic solutions must be tolerant to nuisance novelty, and learn over time in the face of novelty. This paper 1) formalizes the definition of novelty in HAR building upon the prior definition of novelty in classification tasks, 2) proposes an incremental open world learning (OWL) protocol and applies it to the Kinetics datasets to generate a new benchmark KOWL-718, 3) analyzes the performance of current stateof-the-art HAR models when novelty is introduced over time, 4) provides a containerized and packaged pipeline for reproducing the OWL protocol and for modifying for any future updates to Kinetics. The experimental analysis includes an ablation study of how the different models perform under various conditions as annotated by Kinetics-AVA. The code may be used to analyze different annotations and subsets of the Kinetics datasets in an incremental open world fashion, as well as be extended as further updates to Kinetics are released.<\/jats:p>","DOI":"10.24963\/ijcai.2025\/1233","type":"proceedings-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:10:40Z","timestamp":1758269440000},"page":"10959-10959","source":"Crossref","is-referenced-by-count":0,"title":["Human Activity Recognition in an Open World (Abstract Reprint)"],"prefix":"10.24963","author":[{"given":"Derek","family":"Prijatelj","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, University of Notre Dame"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samuel","family":"Grieggs","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Computer Sciences, Indiana University of Pennsylvania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Notre Dame"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dawei","family":"Du","sequence":"additional","affiliation":[{"name":"Kitware, Inc., 1712 Route 9, Suite 300, Clifton Park, NY 12065, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ameya","family":"Shringi","sequence":"additional","affiliation":[{"name":"Kitware, Inc., 1712 Route 9, Suite 300, Clifton Park, NY 12065, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher","family":"Funk","sequence":"additional","affiliation":[{"name":"Kitware, Inc., 1712 Route 9, Suite 300, Clifton Park, NY 12065, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam","family":"Kaufman","sequence":"additional","affiliation":[{"name":"PAR Government, 421 Ridge St, Rome, NY 13440, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Robertson","sequence":"additional","affiliation":[{"name":"PAR Government, 421 Ridge St, Rome, NY 13440, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Walter","family":"Scheirer","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Notre Dame"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"34","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2025","name":"Thirty-Fourth International Joint Conference on Artificial Intelligence {IJCAI-25}","start":{"date-parts":[[2025,8,16]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2025,8,22]]}},"container-title":["Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T11:36:31Z","timestamp":1758627391000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2025\/1233"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2025\/1233","relation":{},"subject":[],"published":{"date-parts":[[2025,9]]}}}