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NIPS
2003
15 years 7 months ago
Learning Non-Rigid 3D Shape from 2D Motion
This paper presents an algorithm for learning the time-varying shape of a non-rigid 3D object from uncalibrated 2D tracking data. We model shape motion as a rigid component (rotat...
Lorenzo Torresani, Aaron Hertzmann, Christoph Breg...
ICTAI
2009
IEEE
16 years 1 months ago
Probabilistic Neural Logic Network Learning: Taking Cues from Neuro-Cognitive Processes
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
Henry Wai Kit Chia, Chew Lim Tan, Sam Yuan Sung
CGF
2008
340views more  CGF 2008»
15 years 6 months ago
Articulated Object Reconstruction and Markerless Motion Capture from Depth Video
We present an algorithm for acquiring the 3D surface geometry and motion of a dynamic piecewise-rigid object using a single depth video camera. The algorithm identifies and tracks...
Yuri Pekelny, Craig Gotsman
NIPS
2004
15 years 7 months ago
Common-Frame Model for Object Recognition
A generative probabilistic model for objects in images is presented. An object consists of a constellation of features. Feature appearance and pose are modeled probabilistically. ...
Pierre Moreels, Pietro Perona
BPSC
2010
285views Business» more  BPSC 2010»
15 years 3 months ago
Crossing the Chasm Between the Real World and Business Process Management
Abstract: While agility is a core challenge in today's competitive business, softwarebased business process modeling and execution approaches often refer to strict and inflexi...
Markus Schief, Benedikt Schmidt