@InProceedings{VilasNovasUsbe:2017:BrDeAp,
               author = "Vilas Novas, Renan and Usberti, F{\'a}bio Luiz",
          affiliation = "Inst. of Comput., Univ. of Campinas (UNICAMP) and Inst. of 
                         Comput., Univ. of Campinas (UNICAMP)",
                title = "Live monitoring in poultry houses: a broiler detection approach",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Computer vision, object detection, broiler chickens, image 
                         processing, automatic monitoring.",
             abstract = "This paper presents a general framework for live detection of 
                         broilers in poultry houses. The challenges for image recognition 
                         of broilers are posted by crowded scenes, poor image quality and 
                         difficulty in acquiring a benchmark of labeled samples. The 
                         proposed framework consists on the use of image thresholding, 
                         morphological transformations, feature engineering, in addition to 
                         supervised and unsupervised learn- ing techniques. Results show 
                         the effectiveness of the proposed framework to detect individual 
                         broilers in a poultry house image. Descriptive attributes related 
                         to the spatial distribution and movement of the broilers can be 
                         extracted using the resultant detections. These attributes can be 
                         used by automated warning systems, for the detection of anomalous 
                         events and thermal stress conditions.",
  conference-location = "Niter{\'o}i, RJ, Brazil",
      conference-year = "17-20 Oct. 2017",
                  doi = "10.1109/SIBGRAPI.2017.35",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2017.35",
             language = "en",
                  ibi = "8JMKD3MGPAW/3PFRLSE",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3PFRLSE",
           targetfile = "PID4958805.pdf",
        urlaccessdate = "2024, May 01"
}