2026-09-27T03:45:27Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/90822026-06-05T20:26:56Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
W. Eric L. Grimson.
DiFranco, David Edward, 1977-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-08-24T19:32:27Z
2005-08-24T19:32:27Z
2000
2000
http://hdl.handle.net/1721.1/9082
46861888
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (p. 71-73).
Recovering the 3D motion of the human body is an important problem in computer vision. Applications that would benefit from 3D motion include physical therapy, computer user interfaces, and 3D animation. Unfortunately, recovering 3D position from one 2D camera is an inherently ill-posed problem. This thesis focuses on recovery of 3D motion of an articulated model using 2D correspondences from an existing 2D tracker. A number of constraints are used to aid in reconstruction: (i) kinematic constraints from a 3D kinematic model, (ii) joint angle limits, (iii) dynamic smoothing, and (iv) key frames. These methods are used successfully to recover 3D motion from video sequences. Also presented is a method for recovering 3D motion from motion capture data, as well as a method for recovering kinematic model connectivity from 2D tracks.
by David Edward DiFranco.
S.B.
M.Eng.
73 p.
5319540 bytes
5319301 bytes
application/pdf
application/pdf
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.
Recovery of 3D articulated motion from 2D correspondences
Recovery of three-dimensional articulated motion from two-dimensional correspondences
Thesis
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<Abstract>Recovering the 3D motion of the human body is an important problem in computer vision. Applications that would benefit from 3D motion include physical therapy, computer user interfaces, and 3D animation. Unfortunately, recovering 3D position from one 2D camera is an inherently ill-posed problem. This thesis focuses on recovery of 3D motion of an articulated model using 2D correspondences from an existing 2D tracker. A number of constraints are used to aid in reconstruction: (i) kinematic constraints from a 3D kinematic model, (ii) joint angle limits, (iii) dynamic smoothing, and (iv) key frames. These methods are used successfully to recover 3D motion from video sequences. Also presented is a method for recovering 3D motion from motion capture data, as well as a method for recovering kinematic model connectivity from 2D tracks.</Abstract>
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