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ICPR
2006
IEEE
16 years 2 months ago
Boosted Markov Chain Monte Carlo Data Association for Multiple Target Detection and Tracking
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
Bo Wu, Gérard G. Medioni, Isaac Cohen, Qian...
165
Voted
IVC
2006
259views more  IVC 2006»
15 years 1 months ago
Object detection using spatial histogram features
In this paper, we propose an object detection approach using spatial histogram features. As spatial histograms consist of marginal distributions of an image over local patches, th...
Hongming Zhang, Wen Gao, Xilin Chen, Debin Zhao
CIKM
2010
Springer
15 years 5 days ago
Partial drift detection using a rule induction framework
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Damon Sotoudeh, Aijun An
SIGSOFT
2009
ACM
16 years 2 months ago
SCA: a semantic conflict analyzer for parallel changes
Parallel changes are becoming increasingly prevalent in the development of large scale software system. To further study the relationship between parallel changes and faults, we h...
Danhua Shao, Sarfraz Khurshid, Dewayne E. Perry
ICPR
2006
IEEE
16 years 2 months ago
Ent-Boost: Boosting Using Entropy Measure for Robust Object Detection
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...
Duy-Dinh Le, Shin'ichi Satoh