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» Sequential Learning of Layered Models from Video
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117
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BMVC
2010
14 years 12 months ago
Probabilistic Latent Sequential Motifs: Discovering Temporal Activity Patterns in Video Scenes
This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns from documents given as word-time occurrences. In this model, docum...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
169
Voted
CRV
2008
IEEE
183views Robotics» more  CRV 2008»
15 years 8 months ago
Robust Real-Time Bi-Layer Video Segmentation Using Infrared Video
In this paper, we propose a novel method for the automatic segmentation of a foreground layer from a natural scene in real time by fusing infrared, color and edge information. Thi...
Qiong Wu, Pierre Boulanger, Walter F. Bischof
ICMCS
2006
IEEE
137views Multimedia» more  ICMCS 2006»
15 years 7 months ago
Relative Depth Layer Extraction for Monoscopic Video by Use of Multidimensional Filter
This paper presents a relative depth layer extraction system for monoscopic video, using multi-line filters and a layer selection algorithm. Main ideas are to extract multiple li...
Jing-Ying Chang, Chao-Chung Cheng, Shao-Yi Chien, ...
ICPR
2006
IEEE
16 years 2 months ago
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models
Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
Datong Chen, Jie Yang
KDD
1998
ACM
190views Data Mining» more  KDD 1998»
15 years 6 months ago
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...
R. Bharat Rao, Scott Rickard, Frans Coetzee