%Aigaion2 BibTeX export from Idiap Publications
%Saturday 23 November 2024 10:32:56 AM

@INPROCEEDINGS{Roy_BMVC2009_2009,
         author = {Roy, Anindya and Marcel, S{\'{e}}bastien},
       projects = {Idiap, MOBIO, SNSF-MULTI},
          month = {9},
          title = {Haar Local Binary Pattern Feature for Fast Illumination Invariant Face Detection},
      booktitle = {British Machine Vision Conference 2009},
           year = {2009},
       crossref = {Roy_Idiap-RR-28-2009},
       abstract = {Face detection is the first step in many visual processing systems like face recognition, emotion recognition and lip reading. In this paper, we propose a novel feature called Haar Local Binary Pattern (HLBP) feature for fast and reliable face detection, particularly in adverse imaging conditions. This binary feature compares bin values of Local Binary Pattern histograms calculated over two adjacent image subregions. These subregions are similar to those in the Haar masks, hence the name of the feature. They capture the region-specific variations of local texture patterns and are boosted using AdaBoost in a framework similar to that proposed by Viola and Jones. Preliminary results obtained on several standard databases show that it competes well with other face detection systems, especially in adverse illumination conditions.},
            pdf = {https://publications.idiap.ch/attachments/papers/2009/Roy_BMVC2009_2009.pdf}
}



crossreferenced publications: 
@TECHREPORT{Roy_Idiap-RR-28-2009,
         author = {Roy, Anindya and Marcel, S{\'{e}}bastien},
       projects = {Idiap, IM2, MOBIO, SNSF-MULTI},
          month = {9},
          title = {Haar Local Binary Pattern Feature for Fast Illumination Invariant Face Detection},
           type = {Idiap-RR},
         number = {Idiap-RR-28-2009},
           year = {2009},
    institution = {Idiap},
       abstract = {Face detection is the first step in many visual processing systems like face recognition, emotion recognition and lip reading. In this paper, we propose a novel feature called Haar Local Binary Pattern (HLBP) feature for fast and reliable face detection, particularly in adverse imaging conditions. This binary feature compares bin values of Local Binary Pattern histograms calculated over two adjacent image subregions. These subregions are similar to those in the Haar masks, hence the name of the feature. They capture the region-specific variations of local texture patterns and are boosted using AdaBoost in a framework similar to that proposed by Viola and Jones. Preliminary results obtained on several standard databases show that it competes well with other face detection systems, especially in adverse illumination conditions.},
            pdf = {https://publications.idiap.ch/attachments/reports/2009/Roy_Idiap-RR-28-2009.pdf}
}