S
Seth Koterba
Researcher at Carnegie Mellon University
Publications - 5
Citations - 288
Seth Koterba is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Camera resectioning & Active appearance model. The author has an hindex of 5, co-authored 5 publications receiving 271 citations.
Papers
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Journal ArticleDOI
An autonomous mobile manipulator for assembly tasks
TL;DR: This paper presents an autonomous mobile manipulator that effectively overcomes inherent system uncertainties and exceptions by utilizing control strategies that employ coordinated control, combine visual and force servoing, and incorporate sophisticated reactive task control.
Proceedings ArticleDOI
Multi-view AAM fitting and camera calibration
TL;DR: An algorithm to calibrate the relative orientation of a set of N > 1 cameras by fitting an AAM to sets of N images by using the human face as a (non-rigid) calibration grid is proposed.
Journal ArticleDOI
Multi-View AAM Fitting and Construction
Krishnan Ramnath,Seth Koterba,Jing Xiao,Changbo Hu,Iain Matthews,Simon Baker,Jeffrey F. Cohn,Takeo Kanade +7 more
TL;DR: It is shown that constructing a 3D face model using non-rigid structure-from-motion suffers from the Bas-Relief ambiguity and may result in a “scaled” (stretched/compressed) model.
Human-Robot Teams for Large-Scale Assembly
Reid Simmons,Sanjiv Singh,Frederik W. Heger,Laura M. Hiatt,Seth Koterba,Nik A. Melchior,Brennan Sellner +6 more
TL;DR: Over the past five years, the architectural framework and tools to coordinate robotic assembly teams, as well as to incorporate the unique skills of remote human operators using an approach that allows authority to “slide” between autonomy and human control at a fine degree of granularity are developed.
Proceedings ArticleDOI
Mobile robotic dynamic tracking for assembly tasks
TL;DR: This paper investigated two tracking methods, one using a laser scanner and the other using a visual fiducial marker, and studied the tracking performance of a mobile base using the pure pursuit algorithm with low pass filtering.