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» Learning Parameterized Models of Image Motion
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PCI
2005
Springer
15 years 5 months 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
WCE
2007
15 years 25 days ago
Motion Detection Based On Accumulative Optical Flow and Double Background Filtering
—Moving object detection is very important for video surveillance. In this paper, we present a new real time motion detection algorithm that is based on the integration of accumu...
Nan Lu, Jihong Wang, Li Yang, Q. Henry Wu
TMI
2010
208views more  TMI 2010»
14 years 6 months ago
Patient-Specific Modeling and Quantification of the Aortic and Mitral Valves From 4-D Cardiac CT and TEE
As decisions in cardiology increasingly rely on non-invasive methods, fast and precise image processing tools have become a crucial component of the analysis workflow. To the best ...
Razvan Ioan Ionasec, Ingmar Voigt, Bogdan Georgesc...
ICVGIP
2004
15 years 1 months ago
Learning Layered Pictorial Structures from Video
We propose a new unsupervised learning method to obtain a layered pictorial structure (LPS) representation of an articulated object from video sequences. It will be seen that this...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
ICIG
2009
IEEE
14 years 9 months ago
Statistical Modeling of Optical Flow
Optical flow estimation is one of the main subjects in computer vision. Many methods developed to compute the motion fields are built using standard heuristic formulation. In this...
Dongmin Ma, Véronique Prinet, Cyril Cassisa