%Aigaion2 BibTeX export from Idiap Publications
%Wednesday 01 May 2024 08:15:13 PM

@INPROCEEDINGS{gatica04a-conf,
         author = {Gatica-Perez, Daniel and Triroj, Napat and Odobez, Jean-Marc and Loui, Alexander and Sun, Ming-Ting},
       projects = {Idiap},
          title = {Assessing Scene Structuring in Consumer Videos},
      booktitle = {Int. Conf. on Image and Video Retrieval (CIVR)},
           year = {2004},
       crossref = {gatica04a},
       abstract = {Scene structuring is a video analysis task for which no common evaluation procedures have been fully adopted. In this paper, we present a methodology to evaluate such task in home videos, which takes into account human judgement, and includes a representative corpus, a set of objective performance measures, and an evaluation protocol. The components of our approach are detailed as follows. First, we describe the generation of a set of home video scene structures produced by multiple people. Second, we define similarity measures that model variations with respect to two factors: human perceptual organization and level of structure granularity. Third, we describe a protocol for evaluation of automatic algorithms based on their comparison to human performance. We illustrate our methodology by assessing the performance of two recently proposed methods: probabilistic hierarchical clustering and spectral clustering.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr04-11.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr04-11.ps.gz},
ipdmembership={vision},
}



crossreferenced publications: 
@TECHREPORT{gatica04a,
         author = {Gatica-Perez, Daniel and Triroj, Napat and Odobez, Jean-Marc and Loui, Alexander and Sun, Ming-Ting},
       projects = {Idiap},
          title = {Assessing Scene Structuring in Consumer Videos},
           type = {Idiap-RR},
         number = {Idiap-RR-11-2004},
           year = {2004},
    institution = {IDIAP},
       abstract = {Scene structuring is a video analysis task for which no common evaluation procedures have been fully adopted. In this paper, we present a methodology to evaluate such task in home videos, which takes into account human judgement, and includes a representative corpus, a set of objective performance measures, and an evaluation protocol. The components of our approach are detailed as follows. First, we describe the generation of a set of home video scene structures produced by multiple people. Second, we define similarity measures that model variations with respect to two factors: human perceptual organization and level of structure granularity. Third, we describe a protocol for evaluation of automatic algorithms based on their comparison to human performance. We illustrate our methodology by assessing the performance of two recently proposed methods: probabilistic hierarchical clustering and spectral clustering.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr04-11.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr04-11.ps.gz},
ipdmembership={vision},
}