2026-09-19T00:53:14Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/910892022-01-13T07:54:01Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Seth Teller.
Hayden, David S. (David Scott)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-10-21T17:25:28Z
2014-10-21T17:25:28Z
2014
2014
http://hdl.handle.net/1721.1/91089
892722087
Thesis: S.M. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
41
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 73-76).
This work presents an end-to-end wearable system designed to learn and assist its (potentially blind) wearers with daily social interactions. In particular, it visually identifies nearby acquaintances and provides timely, discreet notifications of their presence to the wearer. Offline, the system learns the people with whom the wearer interacts by automatically detecting social interactions through egocentric audio, video and accelerometer data and querying the wearer for the identities of persons unknown to the system.
by David S. Hayden.
S.M. in Computer Science and Engineering
76 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Wearable-assisted social interaction as assistive technology for the blind
Thesis
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