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» Activity based surveillance video content modelling
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CVPR
2009
IEEE
16 years 4 months ago
Observe Locally, Infer Globally: a Space-Time MRF for Detecting Abnormal Activities with Incremental Updates
We propose a space-time Markov Random Field (MRF) model to detect abnormal activities in video. The nodes in the MRF graph correspond to a grid of local regions in the video fra...
Jaechul Kim (University of Texas at Austin), Krist...
AINA
2009
IEEE
15 years 4 months ago
Content-Adaptive Robust H.264/SVC Video Communications over 802.11e Networks
In this paper we present a low-complexity traffic prioritization strategy for video transmission using the H.264 scalable video coding (SVC) standard over 802.11e wireless networ...
Dario Gallucci, Attilio Fiandrotti, Enrico Masala,...
72
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AVSS
2006
IEEE
15 years 3 months ago
Learning Foveal Sensing Strategies in Unconstrained Surveillance Environments
In this paper we report on techniques for automatically learning foveal sensing strategies for an active pan-tiltzoom camera. The approach uses reinforcement learning to discover ...
Andrew D. Bagdanov, Alberto Del Bimbo, Walter Nunz...
IVC
2010
143views more  IVC 2010»
14 years 8 months ago
Video-based face model fitting using Adaptive Active Appearance Model
Active Appearance Model (AAM) represents the shape and appearance of an object via two low-dimensional subspaces, one for shape and one for appearance. AAM for facial images is cu...
Xiaoming Liu
SP
2008
IEEE
133views Security Privacy» more  SP 2008»
15 years 4 months ago
ClearShot: Eavesdropping on Keyboard Input from Video
Eavesdropping on electronic communication is usually prevented by using cryptography-based mechanisms. However, these mechanisms do not prevent one from obtaining private informat...
Davide Balzarotti, Marco Cova, Giovanni Vigna