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» A Probabilistic Background Model for Tracking
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ECIR
2009
Springer
15 years 9 months ago
Risk-Aware Information Retrieval
Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...
Jianhan Zhu, Jun Wang, Michael J. Taylor, Ingemar ...
ICIP
2007
IEEE
16 years 1 months ago
Hierarchical Feature Fusion for Visual Tracking
A new method for object tracking in video sequences is presented. This method exploits the benefits of particle filters to tackle the multimodal distributions emerging from clutte...
Alexandros Makris, Dimitrios I. Kosmopoulos, Stavr...
EMNLP
2007
15 years 1 months ago
Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
We present a data-driven variant of the LR algorithm for dependency parsing, and extend it with a best-first search for probabilistic generalized LR dependency parsing. Parser act...
Kenji Sagae, Jun-ichi Tsujii
PAMI
2012
13 years 2 months ago
Scribble Tracker: A Matting-Based Approach for Robust Tracking
—Model updating is a critical problem in tracking. Inaccurate extraction of the foreground and background information in model adaptation would cause the model to drift and degra...
Jialue Fan, Xiaohui Shen, Ying Wu
IWCM
2004
Springer
15 years 5 months ago
Tracking Complex Objects Using Graphical Object Models
We present a probabilistic framework for component-based automatic detection and tracking of objects in video. We represent objects as spatio-temporal two-layer graphical models, w...
Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael J...