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SUMMARY:3D Matching of resource vision tracking trajectories   - Eirini Ko
 nstantinou - Construction Engineering Student
DTSTART:20151204T150000Z
DTEND:20151204T153000Z
UID:TALK61322@talks.cam.ac.uk
CONTACT:Lorna Everett
DESCRIPTION:Issues related to management and workforce play a key role in 
 the productivity gap of construction and manufacturing. Both issues are di
 rectly related to the way productivity is measured. Current measurement me
 thods tend to be ineffective because they are labour intensive\, costly an
 d prone to human errors whereas they are mainly reactive processes initiat
 ed after the detection of a negatively influencing factor. So far\, resear
 ch efforts in automating the measuring process have not achieved full auto
 mation because they require prior knowledge of the type of tasks performed
  in specific working zones. This is highly associated with the lack of dep
 th information. For this purpose\, we propose a computationally efficient 
 computer vision method for matching construction workers across different 
 frames based on epipolar geometry and past motion 2D data. The main result
  of this process is to provide a method for the acquisition of the 4D feat
 ures (x\, y\, z\, t) that compose the detailed profile of a construction a
 ctivity in terms of both time and space. 
LOCATION:Cambridge University Engineering Department\, LR3B
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