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@InProceedings{CejnogJrCampElui:2018:InHaTh,
               author = "Cejnog, Luciano Walenty Xavier and Jr. , Roberto Marcondes Cesar 
                         and Campos, Te{\'o}filo de and Elui, Val{\'e}ria Meirelles 
                         Carril",
          affiliation = "Departamento de Ci{\^e}ncia da Computa{\c{c}}{\~a}o, IME/USP 
                         and Departamento de Ci{\^e}ncia da Computa{\c{c}}{\~a}o, 
                         IME/USP and Departamento de Ci{\^e}ncia da 
                         Computa{\c{c}}{\~a}o, Universidade de Bras{\'{\i}}lia and 
                         Departamento de Terapia Ocupacional, FMUSP Ribeir{\~a}o Preto",
                title = "Injured hand therapy evaluation using hand tracking",
            booktitle = "Proceedings...",
                 year = "2018",
               editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and 
                         Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and 
                         Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez, 
                         Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de 
                         and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa, 
                         Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus, 
                         Klaus de and Scheer, Sergio",
         organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "hand tracking, hand pose estimation, computer vision, depth 
                         images.",
             abstract = "Hand tracking is a challenging problem in computer vision that has 
                         recently gained relevance with the development of cheap 
                         consumer-level depth cameras and virtual reality devices. The 
                         objective is to identify a hand model in a scene and track the 
                         model accurately in a sequence of frames. The main proposal of 
                         this project is the development of a framework for hand tracking 
                         and gesture analysis, using a 3D model able to express different 
                         patterns of hand pose. Methods for data acquisition, learning 
                         model parameters, hand tracking/detection in video sequences and 
                         movement analysis will be developed. Here we describe the 
                         formation of the dataset and the first tests with hand pose 
                         estimation methods. Future steps include the development of hand 
                         detection, pose estimation and tracking methods based on 
                         state-of-art, as well as the assessment of movement quantities 
                         using the joint angles from the skeletons estimated by the pose 
                         estimation methods.",
  conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
      conference-year = "Oct. 29 - Nov. 1, 2018",
             language = "en",
                  ibi = "8JMKD3MGPAW/3S4SNFL",
                  url = "http://urlib.net/rep/8JMKD3MGPAW/3S4SNFL",
           targetfile = "SIBGRAPI_WIP_2018(3).pdf",
        urlaccessdate = "2020, Dec. 02"
}


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