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ICMLA
2008
14 years 11 months ago
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
Silvia Chiappa
GMP
2008
IEEE
143views Solid Modeling» more  GMP 2008»
14 years 10 months ago
Space-Time Curve Analogies for Motion Editing
Abstract. This paper presents a method for analogizing high-dimensional spacetime curves, and shows how it can be used to transform a motion sequence into new content and styles ac...
Yuan Wu, Hongxin Zhang, Chao Song, Hujun Bao
CAIP
1999
Springer
115views Image Analysis» more  CAIP 1999»
15 years 2 months ago
EigenHistograms: Using Low Dimensional Models of Color Distribution for Real Time Object Recognition
Abstract. Distribution of object colors has been used in computer vision for recognition and indexing. Most of the recent approaches to this problem have been focused on de ning op...
Jordi Vitrià, Petia Radeva, Xavier Binefa
CGF
2011
14 years 1 months ago
Visual Exploration of Time-Series Data with Shape Space Projections
Time-series data is a common target for visual analytics, as they appear in a wide range of application domains. Typical tasks in analyzing time-series data include identifying cy...
Matthew O. Ward, Zhenyu Guo
CSDA
2006
191views more  CSDA 2006»
14 years 9 months ago
Forecasting daily time series using periodic unobserved components time series models
We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend, seasonal and irregu...
Siem Jan Koopman, Marius Ooms