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» Evaluating algorithms that learn from data streams
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ICIAR
2009
Springer
15 years 2 months ago
3D Human Pose Estimation from Static Images Using Local Features and Discriminative Learning
In this paper an approach to recover the 3D human body pose from static images is proposed. We adopt a discriminative learning technique to directly infer the 3D pose from appearan...
Suman Sedai, Farid Flitti, Mohammed Bennamoun, Du ...
SIGIR
2011
ACM
14 years 7 months ago
Learning to rank from a noisy crowd
We study how to best use crowdsourced relevance judgments learning to rank [1, 7]. We integrate two lines of prior work: unreliable crowd-based binary annotation for binary classi...
Abhimanu Kumar, Matthew Lease
JSAC
2010
146views more  JSAC 2010»
14 years 11 months ago
NLOS identification and mitigation for localization based on UWB experimental data
Abstract--Sensor networks can benefit greatly from locationawareness, since it allows information gathered by the sensors to be tied to their physical locations. Ultra-wide bandwid...
Stefano Maranò, Wesley M. Gifford, Henk Wym...
IJAMC
2010
118views more  IJAMC 2010»
15 years 3 months ago
Bandwidth-aware Peer-to-Peer 3D streaming
—Peer-to-Peer streaming support for 3D content (i.e., P2P 3D streaming) has recently been proposed to provide affordable and real-time virtual environment (VE) content delivery. ...
Chien-Hao Chien, Shun-Yun Hu, Jehn-Ruey Jiang, Chu...
ECCV
2002
Springer
16 years 6 months ago
Learning Shape from Defocus
We present a novel method for inferring three-dimensional shape from a collection of defocused images. It is based on the observation that defocused images are the null-space of ce...
Paolo Favaro, Stefano Soatto