{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105242"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105242","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Headtrack: Tracking head orientation using wireless signals","abstract":"Estimating and tracking the head orientation of the user is an important problem for numerous mobile computing applications. Current solutions to the problem require deploying infrastructure (namely, cameras and lasers) along with expensive (IMU) sensors. These infrastructure-based approaches bound the user to a limited area of tracking and also disable the portability and mobility of the user. This work presents HeadTrack and explores the feasibility of designing a necklace-like wearable consisting of a headset and a chest-piece that can be used to estimate the user's head orientation using wireless (radio frequency) signals. The core problem presented in this thesis is to accurately estimate multiple distances between the chest-piece on the torso and the headset using the ultra-wide band (UWB) radios. Such a wearable not only enables portability but also mobility by decoupling the user's head motion from the body motion. Although the ultra-wide band radios have a 1GHz bandwidth and high-speed clocks, they are unable to do sub-centimeter ranging. We improve the typical ~10cm accuracy of the UWB radios by introducing a wired path between the transmitters and the receivers to serve as a reference point. We split the signal at the transmitter and route it through the wired as well as the wireless paths to improve the accuracy to about 5mm. We use ViCon to collect the ground truth for our experiments and evaluate our system. HeadTrack uses an IMU to resolve the phase wrap ambiguities and is able to track the head orientation of the user with an accuracy of 6.5 degrees. HeadTrack provides a wearable, occlusion-free, portable, and cost-effective solution to the problem of head orientation tracking with a bounded and non-diverging error.","abstract_html":"Estimating and tracking the head orientation of the user is an important problem for numerous mobile computing applications. Current solutions to the problem require deploying infrastructure (namely, cameras and lasers) along with expensive (IMU) sensors. These infrastructure-based approaches bound the user to a limited area of tracking and also disable the portability and mobility of the user. This work presents HeadTrack and explores the feasibility of designing a necklace-like wearable consisting of a headset and a chest-piece that can be used to estimate the user's head orientation using wireless (radio frequency) signals. The core problem presented in this thesis is to accurately estimate multiple distances between the chest-piece on the torso and the headset using the ultra-wide band (UWB) radios. Such a wearable not only enables portability but also mobility by decoupling the user's head motion from the body motion. Although the ultra-wide band radios have a 1GHz bandwidth and high-speed clocks, they are unable to do sub-centimeter ranging. We improve the typical ~10cm accuracy of the UWB radios by introducing a wired path between the transmitters and the receivers to serve as a reference point. We split the signal at the transmitter and route it through the wired as well as the wireless paths to improve the accuracy to about 5mm. We use ViCon to collect the ground truth for our experiments and evaluate our system. HeadTrack uses an IMU to resolve the phase wrap ambiguities and is able to track the head orientation of the user with an accuracy of 6.5 degrees. HeadTrack provides a wearable, occlusion-free, portable, and cost-effective solution to the problem of head orientation tracking with a bounded and non-diverging error.","abstract_has_math":false,"creators":["Agrawal, Amod Kant"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Choudhury, Romit R."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:48:22Z","date_published":"2019-08-23T20:48:22Z","updated_at":"2026-07-22T22:24:44Z","subjects":["ultra","wide","band","UWB","tracking","head","orientation","radio","frequency","ultrawide","mobile computing","RF sensing","sensing","augmented","virtual","reality","wearable","mobile","headtrack","localization","ranging","yaw","pitch","roll","AR","VR","earables","earable","portable","vicon","distance","integer","ambiguity","inertial","measurement","unit","IMU"],"languages":["en"],"rights":["Copyright 2019 Amod Kant Agrawal"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105242","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Choudhury, Romit R."]},{"key":"dc:creator","label":"Author","values":["Agrawal, Amod Kant"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T20:48:22Z","2021-08-24T09:15:24Z","2019-04-22","2019-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"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":["ultra","wide","band","UWB","tracking","head","orientation","radio","frequency","ultrawide","mobile computing","RF sensing","sensing","augmented","virtual","reality","wearable","mobile","headtrack","localization","ranging","yaw","pitch","roll","AR","VR","earables","earable","portable","vicon","distance","integer","ambiguity","inertial","measurement","unit","IMU"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Amod Kant Agrawal"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105242"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Estimating and tracking the head orientation of the user is an important problem for numerous mobile computing applications. Current solutions to the problem require deploying infrastructure (namely, cameras and lasers) along with expensive (IMU) sensors. These infrastructure-based approaches bound the user to a limited area of tracking and also disable the portability and mobility of the user. This work presents HeadTrack and explores the feasibility of designing a necklace-like wearable consisting of a headset and a chest-piece that can be used to estimate the user's head orientation using wireless (radio frequency) signals. The core problem presented in this thesis is to accurately estimate multiple distances between the chest-piece on the torso and the headset using the ultra-wide band (UWB) radios. Such a wearable not only enables portability but also mobility by decoupling the user's head motion from the body motion. Although the ultra-wide band radios have a 1GHz bandwidth and high-speed clocks, they are unable to do sub-centimeter ranging. We improve the typical ~10cm accuracy of the UWB radios by introducing a wired path between the transmitters and the receivers to serve as a reference point. We split the signal at the transmitter and route it through the wired as well as the wireless paths to improve the accuracy to about 5mm. We use ViCon to collect the ground truth for our experiments and evaluate our system. HeadTrack uses an IMU to resolve the phase wrap ambiguities and is able to track the head orientation of the user with an accuracy of 6.5 degrees. 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Current solutions to the problem require deploying infrastructure (namely, cameras and lasers) along with expensive (IMU) sensors. These infrastructure-based approaches bound the user to a limited area of tracking and also disable the portability and mobility of the user. This work presents HeadTrack and explores the feasibility of designing a necklace-like wearable consisting of a headset and a chest-piece that can be used to estimate the user's head orientation using wireless (radio frequency) signals. The core problem presented in this thesis is to accurately estimate multiple distances between the chest-piece on the torso and the headset using the ultra-wide band (UWB) radios. Such a wearable not only enables portability but also mobility by decoupling the user's head motion from the body motion. Although the ultra-wide band radios have a 1GHz bandwidth and high-speed clocks, they are unable to do sub-centimeter ranging. We improve the typical ~10cm accuracy of the UWB radios by introducing a wired path between the transmitters and the receivers to serve as a reference point. We split the signal at the transmitter and route it through the wired as well as the wireless paths to improve the accuracy to about 5mm. We use ViCon to collect the ground truth for our experiments and evaluate our system. HeadTrack uses an IMU to resolve the phase wrap ambiguities and is able to track the head orientation of the user with an accuracy of 6.5 degrees. HeadTrack provides a wearable, occlusion-free, portable, and cost-effective solution to the problem of head orientation tracking with a bounded and non-diverging error.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","The student, Amod Agrawal, accepted the attached license on 2019-04-22 at 11:28.","The student, Amod Agrawal, submitted this Thesis for approval on 2019-04-22 at 11:48.","This Thesis was approved for publication on 2019-04-22 at 14:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13816 on 2019-08-22 at 16:23:29","Made available in DSpace on 2019-08-23T20:48:22Z (GMT). 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