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ICMLA
2007
14 years 11 months ago
Uncertainty optimization for robust dynamic optical flow estimation
We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of ...
Volker Willert, Marc Toussaint, Julian Eggert, Edg...
RC
2007
78views more  RC 2007»
14 years 9 months ago
Monte-Carlo-Type Techniques for Processing Interval Uncertainty, and Their Potential Engineering Applications
Abstract. In engineering applications, we need to make decisions under uncertainty. Traditionally, in engineering, statistical methods are used, methods assuming that we know the p...
Vladik Kreinovich, Jan Beck, Carlos Ferregut, Arac...
JSAC
2007
104views more  JSAC 2007»
14 years 9 months ago
Tomlinson-Harashima Precoding for Broadcast Channels with Uncertainty
— We consider the design of Tomlinson-Harashima (TH) precoders for broadcast channels in the presence of channel uncertainty. For systems in which uplink-downlink reciprocity is ...
Michael Botros Shenouda, Timothy N. Davidson
ACCV
2006
Springer
15 years 3 months ago
A Novel Robust Statistical Method for Background Initialization and Visual Surveillance
In many visual tracking and surveillance systems, it is important to initialize a background model using a training video sequence which may include foreground objects. In such a c...
Hanzi Wang, David Suter
CVPR
2010
IEEE
15 years 3 months ago
Secrets of Optical Flow Estimation and Their Principles
The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however...
Deqing Sun, Stefan Roth, Michael Black