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PCI
2005
Springer
16 years 10 days ago
Unsupervised Learning of Multiple Aspects of Moving Objects from Video
A popular framework for the interpretation of image sequences is based on the layered model; see e.g. Wang and Adelson [8], Irani et al. [2]. Jojic and Frey [3] provide a generativ...
Michalis K. Titsias, Christopher K. I. Williams
WAPCV
2004
Springer
16 years 5 days ago
Visual Attention for Object Recognition in Spatial 3D Data
In this paper, we present a new recognition system for the fast detection and classification of objects in spatial 3D data. The system consists of two main components: A biologic...
Simone Frintrop, Andreas Nüchter, Hartmut Sur...
MVA
1992
166views Computer Vision» more  MVA 1992»
15 years 8 months ago
Estimation and Interpretation of Optical Flow Fields for Counting Moving Objects
The main goal of sequence analysis is the motion estimation of moving objects which are present in the scene. One of the most important approaches for motion estimation is based o...
Alberto Del Bimbo, Paolo Nesi, Jorge L. C. Sanz
TIP
2008
69views more  TIP 2008»
15 years 6 months ago
An Efficient Phase and Object Estimation Scheme for Phase-Diversity Time Series Data
We present a two-stage method for obtaining both phase and object estimates from phase-diversity time series data. In the first stage, the phases are estimated for each time frame...
Johnathan M. Bardsley
TNN
2008
141views more  TNN 2008»
15 years 6 months ago
MPCA: Multilinear Principal Component Analysis of Tensor Objects
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...