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» Evaluating algorithms that learn from data streams
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CVPR
2012
IEEE
13 years 10 months ago
Contextual Boost for Pedestrian Detection
Pedestrian detection from images is an important and yet challenging task. The conventional methods usually identify human figures using image features inside the local regions. In...
Yuanyuan Ding, Jing Xiao
ICDM
2005
IEEE
271views Data Mining» more  ICDM 2005»
16 years 27 days ago
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the r...
Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu
DEXA
2005
Springer
80views Database» more  DEXA 2005»
16 years 24 days ago
Optimizing I/O Costs of Multi-dimensional Queries Using Bitmap Indices
Bitmap indices are efficient data structures for processing complex, multi-dimensional queries in data warehouse applications and scientific data analysis. For high-cardinality at...
Doron Rotem, Kurt Stockinger, Kesheng Wu
ICPR
2006
IEEE
16 years 8 months ago
Automatic Acquisition of Context Models and its Application to Video Surveillance
This paper addresses the problem of automatically acquiring context models from data. Context and human behavior are represented using a state model, called situation model. This ...
James L. Crowley, Oliver Brdiczka, Patrick Reignie...
ICIP
2009
IEEE
16 years 8 months ago
Corner-based Background Segmentation Using Adaptive Resonance Theory
A correct video segmentation, namely the detection of moving objects within a scene plays a very important role in many application in safety, surveillance, trafic monitoring and ...