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CIKM
2009
Springer
15 years 9 months ago
Mining data streams with periodically changing distributions
Dynamic data streams are those whose underlying distribution changes over time. They occur in a number of application domains, and mining them is important for these applications....
Yingying Tao, M. Tamer Özsu
ACCV
2006
Springer
16 years 20 hour ago
Probabilistic Modeling for Structural Change Inference
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
Wei Liu, Véronique Prinet
PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
15 years 11 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
CVPR
2012
IEEE
13 years 8 months ago
Part-based multiple-person tracking with partial occlusion handling
Single camera-based multiple-person tracking is often hindered by difficulties such as occlusion and changes in appearance. In this paper, we address such problems by proposing a...
Guang Shu, Afshin Dehghan, Omar Oreifej, Emily Han...
ICCV
2001
IEEE
16 years 8 months ago
Real-Time Feature Tracking and Outlier Rejection with Changes in Illumination
We develop an efficient algorithm to track point features supported by image patches undergoing affine deformations and changes in illumination. The algorithm is based on a combin...
Hailin Jin, Paolo Favaro, Stefano Soatto