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CVPR
2012
IEEE
13 years 9 months ago
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Bolei Zhou, Xiaogang Wang, Xiaoou Tang
TKDE
2012
190views Formal Methods» more  TKDE 2012»
13 years 9 months ago
Scalable Learning of Collective Behavior
—This study of collective behavior is to understand how individuals behave in a social networking environment. Oceans of data generated by social media like Facebook, Twitter, Fl...
Lei Tang, Xufei Wang, Huan Liu
ICCV
2007
IEEE
16 years 8 months ago
Learning to Find Object Boundaries Using Motion Cues
While great strides have been made in detecting and localizing specific objects in natural images, the bottom-up segmentation of unknown, generic objects remains a difficult chall...
Andrew N. Stein, Derek Hoiem, Martial Hebert
ICIP
2005
IEEE
16 years 8 months ago
Learning spatially-variable filters for super-resolution of text
Images magnified by standard methods display a degradation of detail that is particularly noticeable in the blurry edges of text. Current super-resolution algorithms address the l...
Adrian Corduneanu, John C. Platt
HRI
2010
ACM
16 years 1 months ago
Investigating multimodal real-time patterns of joint attention in an hri word learning task
Abstract—Joint attention – the idea that humans make inferences from observable behaviors of other humans by attending to the objects and events that these others humans attend...
Chen Yu, Matthias Scheutz, Paul W. Schermerhorn