{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124581"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124581","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"A survey of IMU based cross-modal transfer learning in human activity recognition","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_has_math":false,"creators":["Kamboj, Abhi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Do, Minh"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:02Z","subjects":["Inertial Measurement Units","Human Action Recognition","Transfer Learning","Cross-modal Learning","Multimodal Learning","Sensor Fusion"],"languages":["en","eng"],"rights":["Copyright 2024 Abhi Kamboj"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124581","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Do, Minh"]},{"key":"dc:creator","label":"Author","values":["Kamboj, Abhi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-04-30"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Inertial Measurement Units","Human Action Recognition","Transfer Learning","Cross-modal Learning","Multimodal Learning","Sensor Fusion"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2024 Abhi Kamboj"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124581"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Abhi Kamboj, accepted the attached license on 2024-04-25 at 13:22.","The student, Abhi Kamboj, submitted this Thesis for approval on 2024-04-26 at 09:50.","This Thesis was approved for publication on 2024-04-30 at 09:04.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20640 on 2024-09-16 at 00:44:46","Despite living in a multi-sensory world, most AI models are limited to textual and visual understanding of human motion and behavior. Inertial measurement units (IMUs) provide a salient signal to understand human motion; however, in practice, they have been understudied due to numerous difficulties, including the uniterpretability and lack of data. In fact, full situational awareness of human motion could best be understood through a combination of sensors. In this survey, we investigate how knowledge can be transferred and utilized amongst modalities for Human Activity or Action Recognition (HAR), i.e. cross-modality transfer learning. We motivate the importance and potential of IMU data and its applicability in cross-modality learning as well as the importance of studying the HAR problem. We categorize HAR related tasks by time and abstractness and then compare various types of multimodal HAR datasets. We also distinguish and expound on many related but inconsistently used terms in the literature, such as transfer learning, domain adaptation, representation learning, sensor fusion, and multimodal learning, and describe how cross-modal learning fits with all these concepts. Then, we review the literature on IMU-based cross-modal transfer for HAR. The two main approaches for cross-modal transfer are instance-based transfer, where instances of one modality are mapped to another (e.g. knowledge is transferred in the input space), or feature-based transfer, where the model relates the modalities in an intermediate latent space (e.g. knowledge is transferred in the feature space). Finally, we discuss future research directions and applications in cross-modal HAR."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["A survey of IMU based cross-modal transfer learning in human activity recognition"]}]}],"canonical_facts":{"dc:contributor":["Do, Minh"],"dc:creator":["Kamboj, Abhi"],"dc:date":["2024-05","2024-04-30"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Abhi Kamboj, accepted the attached license on 2024-04-25 at 13:22.","The student, Abhi Kamboj, submitted this Thesis for approval on 2024-04-26 at 09:50.","This Thesis was approved for publication on 2024-04-30 at 09:04.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20640 on 2024-09-16 at 00:44:46","Despite living in a multi-sensory world, most AI models are limited to textual and visual understanding of human motion and behavior. Inertial measurement units (IMUs) provide a salient signal to understand human motion; however, in practice, they have been understudied due to numerous difficulties, including the uniterpretability and lack of data. In fact, full situational awareness of human motion could best be understood through a combination of sensors. In this survey, we investigate how knowledge can be transferred and utilized amongst modalities for Human Activity or Action Recognition (HAR), i.e. cross-modality transfer learning. We motivate the importance and potential of IMU data and its applicability in cross-modality learning as well as the importance of studying the HAR problem. We categorize HAR related tasks by time and abstractness and then compare various types of multimodal HAR datasets. We also distinguish and expound on many related but inconsistently used terms in the literature, such as transfer learning, domain adaptation, representation learning, sensor fusion, and multimodal learning, and describe how cross-modal learning fits with all these concepts. Then, we review the literature on IMU-based cross-modal transfer for HAR. The two main approaches for cross-modal transfer are instance-based transfer, where instances of one modality are mapped to another (e.g. knowledge is transferred in the input space), or feature-based transfer, where the model relates the modalities in an intermediate latent space (e.g. knowledge is transferred in the feature space). Finally, we discuss future research directions and applications in cross-modal HAR."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124581"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Abhi Kamboj"],"dc:subject":["Inertial Measurement Units","Human Action Recognition","Transfer Learning","Cross-modal Learning","Multimodal Learning","Sensor Fusion"],"dc:title":["A survey of IMU based cross-modal transfer learning in human activity recognition"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}