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» Sequential Learning of Layered Models from Video
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BMVC
2010
14 years 7 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...
CRV
2008
IEEE
183views Robotics» more  CRV 2008»
15 years 4 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 3 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
15 years 10 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 1 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