%Aigaion2 BibTeX export from Idiap Publications
%Wednesday 19 June 2024 12:52:34 AM

@ARTICLE{SWV00,
         author = {Shearer, Kim and Wong, Kirrily D and Venkatesh, Svetha},
       projects = {Idiap},
          title = {Combining multiple tracking algorithms for improved general performance},
        journal = {Pattern Recognition},
         volume = {34},
         number = {06},
           year = {2000},
       crossref = {swv00tr},
       abstract = {Automated tracking of objects through a sequence of images has remained one of the difficult problems in computer vision. Numerous algorithms and techniques have been proposed for this task. Some algorithms perform well in restricted environments, such as tracking using stationary cameras, but a general solution is not currently available. A frequent problem is that when an algorithm is refined for one application, it becomes unsuitable for other applications. This paper proposes a general tracking system based on a different approach. Rather than refine one algorithm for a specific tracking task, two tracking algorithms are employed, and used to correct each other during the tracking task. By choosing the two algorithms such that they have complementary failure modes, a robust algorithm is created without increased specialisation.},
            pdf = {https://publications.idiap.ch/attachments/reports/2000/rr00-13.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2000/rr00-13.ps.gz},
ipdmembership={vision},
}



crossreferenced publications: 
@TECHREPORT{SWV00TR,
         author = {Shearer, Kim and Wong, Kirrily D and Venkatesh, Svetha},
       projects = {Idiap},
          title = {Combining multiple tracking algorithms for improved general performance},
           type = {Idiap-RR},
         number = {Idiap-RR-13-2000},
           year = {2000},
    institution = {IDIAP},
       abstract = {Automated tracking of objects through a sequence of images has remained one of the difficult problems in computer vision. Numerous algorithms and techniques have been proposed for this task. Some algorithms perform well in restricted environments, such as tracking using stationary cameras, but a general solution is not currently available. A frequent problem is that when an algorithm is refined for one application, it becomes unsuitable for other applications. This paper proposes a general tracking system based on a different approach. Rather than refine one algorithm for a specific tracking task, two tracking algorithms are employed, and used to correct each other during the tracking task. By choosing the two algorithms such that they have complementary failure modes, a robust algorithm is created without increased specialisation.},
            pdf = {https://publications.idiap.ch/attachments/reports/2000/rr00-13.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2000/rr00-13.ps.gz},
ipdmembership={vision},
}