DocumentCode :
888401
Title :
Biotracking gives back to nature
Author :
Voth, Danna
Volume :
19
Issue :
1
fYear :
2004
Firstpage :
6
Lastpage :
7
Abstract :
We develop a biotracking software, which helps biologists track animals and insects and study their behavior by analyzing videotaped data. To biologists, whose observation and analysis methods are time-consuming, the automated system has been a boon. The idea for the biotracking software was conceived while studying robots. We use hidden Markov models (HMMs) to track the moving robots and extract the behaviors from their motion. The technology also has broader applications; it can be applied to any large group of observable and trackable moving agents. The program tracks objects of the ant color from video frame to video frame. The program makes it easy to view the bee activity logs and label the types of bee activity by combining HMM learning with k-nearest neighbor classification.
Keywords :
biology computing; hidden Markov models; learning (artificial intelligence); multi-agent systems; HMM learning; bee activity log; biotracking software; hidden Markov model; k-nearest neighbor classification; multiagent systems; videotaped data; Biological information theory; Biology; Books; Collaboration; Humans; Machine vision; Particle tracking; Profitability; Refrigeration; System testing;
fLanguage :
English
Journal_Title :
Intelligent Systems, IEEE
Publisher :
ieee
ISSN :
1541-1672
Type :
jour
DOI :
10.1109/MIS.2004.1265877
Filename :
1265877
Link To Document :
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