{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/108978"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/108978","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Capturing the human figure through a wall","abstract":"We present RF-Capture, a system that captures the human figure - i.e., a coarse skeleton - through a wall. RF-Capture tracks the 3D positions of a person's limbs and body parts even when the person is fully occluded from its sensor, and does so without placing any markers on the subject's body. In designing RF-Capture, we built on recent advances in wireless research, which have shown that certain radio frequency (RF) signals can traverse walls and reflect off the human body, allowing for the detection of human motion through walls. In contrast to these past systems which abstract the entire human body as a single point and find the overall location of that point through walls, we show how we can reconstruct various human body parts and stitch them together to capture the human figure. We built a prototype of RF-Capture and tested it on 15 subjects. Our results show that the system can capture a representative human figure through walls and use it to distinguish between various users.","abstract_html":"We present RF-Capture, a system that captures the human figure - i.e., a coarse skeleton - through a wall. RF-Capture tracks the 3D positions of a person&#x27;s limbs and body parts even when the person is fully occluded from its sensor, and does so without placing any markers on the subject&#x27;s body. In designing RF-Capture, we built on recent advances in wireless research, which have shown that certain radio frequency (RF) signals can traverse walls and reflect off the human body, allowing for the detection of human motion through walls. In contrast to these past systems which abstract the entire human body as a single point and find the overall location of that point through walls, we show how we can reconstruct various human body parts and stitch them together to capture the human figure. We built a prototype of RF-Capture and tested it on 15 subjects. Our results show that the system can capture a representative human figure through walls and use it to distinguish between various users.","abstract_has_math":false,"creators":["Hsu, Chen-Yu, Ph. D. Massachusetts Institute of Technology"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Dina Katabi."],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017","date_published":"2017","updated_at":"2026-07-22T22:22:22Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/108978","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Dina Katabi."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."]},{"key":"dc:creator","label":"Author","values":["Hsu, Chen-Yu, Ph. D. Massachusetts Institute of Technology"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-05-11T19:58:52Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-05-11T19:58:52Z"]},{"key":"dc:date.issued","label":"Date","values":["2017"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical Engineering and Computer Science."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/108978"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 49-53)."]},{"key":"dc:description.abstract","label":"Abstract","values":["We present RF-Capture, a system that captures the human figure - i.e., a coarse skeleton - through a wall. RF-Capture tracks the 3D positions of a person's limbs and body parts even when the person is fully occluded from its sensor, and does so without placing any markers on the subject's body. In designing RF-Capture, we built on recent advances in wireless research, which have shown that certain radio frequency (RF) signals can traverse walls and reflect off the human body, allowing for the detection of human motion through walls. In contrast to these past systems which abstract the entire human body as a single point and find the overall location of that point through walls, we show how we can reconstruct various human body parts and stitch them together to capture the human figure. We built a prototype of RF-Capture and tested it on 15 subjects. Our results show that the system can capture a representative human figure through walls and use it to distinguish between various users."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M. in Computer Science and Engineering"]},{"key":"dc:title","label":"Title","values":["Capturing the human figure through a wall"]}]}],"canonical_facts":{"dc:contributor.advisor":["Dina Katabi."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science"],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Hsu, Chen-Yu, Ph. D. Massachusetts Institute of Technology"],"dc:date.accessioned":["2017-05-11T19:58:52Z"],"dc:date.available":["2017-05-11T19:58:52Z"],"dc:date.issued":["2017"],"dc:description":["Thesis: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.","Cataloged from PDF version of thesis.","Includes bibliographical references (pages 49-53)."],"dc:description.abstract":["We present RF-Capture, a system that captures the human figure - i.e., a coarse skeleton - through a wall. RF-Capture tracks the 3D positions of a person's limbs and body parts even when the person is fully occluded from its sensor, and does so without placing any markers on the subject's body. In designing RF-Capture, we built on recent advances in wireless research, which have shown that certain radio frequency (RF) signals can traverse walls and reflect off the human body, allowing for the detection of human motion through walls. In contrast to these past systems which abstract the entire human body as a single point and find the overall location of that point through walls, we show how we can reconstruct various human body parts and stitch them together to capture the human figure. We built a prototype of RF-Capture and tested it on 15 subjects. Our results show that the system can capture a representative human figure through walls and use it to distinguish between various users."],"dc:description.degree":["S.M. in Computer Science and Engineering"],"dc:identifier.uri":["http://hdl.handle.net/1721.1/108978"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Capturing the human figure through a wall"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:22:22Z"}