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ECCV
2002
Springer
16 years 9 months ago
Implicit Probabilistic Models of Human Motion for Synthesis and Tracking
Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
Hedvig Sidenbladh, Michael J. Black, Leonid Sigal
201
Voted
IPPS
2006
IEEE
16 years 1 months ago
A method to improve structural modeling based on conserved domain clusters
—Homology modeling requires an accurate alignment between a query sequence and its homologs with known three-dimensional (3D) information. Current structural modeling techniques ...
Fa Zhang, Lin Xu, Bo Yuan
UIST
1995
ACM
15 years 10 months ago
Visual Interfaces for Solids Modeling
This paper exploresthe useof visualoperatorsfor solidsmodeling. We focus on designing interfaces for free-form operators such as blends, sweeps, and deformations, because these op...
Cindy Grimm, David Pugmire
FLAIRS
2008
15 years 9 months ago
Learning a Probabilistic Model of Event Sequences from Internet Weblog Stories
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...
Mehdi Manshadi, Reid Swanson, Andrew S. Gordon
BMCBI
2008
172views more  BMCBI 2008»
15 years 7 months ago
Compo: composite motif discovery using discrete models
Background: Computational discovery of motifs in biomolecular sequences is an established field, with applications both in the discovery of functional sites in proteins and regula...
Geir Kjetil Sandve, Osman Abul, Finn Drablø...