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» Probabilistic Object Tracking Using Multiple Features
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UAI
2004
13 years 10 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
ICCV
2011
IEEE
12 years 9 months ago
Struck: Structured Output Tracking with Kernels
Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task a...
Sam Hare, Amir Saffari, Philip H.S. Torr
SDM
2007
SIAM
146views Data Mining» more  SDM 2007»
13 years 10 months ago
ROAM: Rule- and Motif-Based Anomaly Detection in Massive Moving Object Data Sets
With recent advances in sensory and mobile computing technology, enormous amounts of data about moving objects are being collected. One important application with such data is aut...
Xiaolei Li, Jiawei Han, Sangkyum Kim, Hector Gonza...
ACMICEC
2003
ACM
125views ECommerce» more  ACMICEC 2003»
14 years 2 months ago
A heuristic bidding strategy for multiple heterogeneous auctions
Online auctions are increasingly being used as a medium to procure goods and services. As the number of auction sites increases, however, consumers will inevitably want to track a...
Patricia Anthony, Nicholas R. Jennings
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 7 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu