@article{SisLab4480,
          volume = {37},
          number = {1},
           title = {Robustify Hand Tracking by Fusing Generative and Discriminative Methods},
          author = {Duc Thao Nguyen and Viet Anh Nguyen and Thanh Ha Le and Thi Duyen Ngo},
       publisher = {VNU},
            year = {2021},
         journal = {VNU Journal of Science: Computer Science and Communication Engineering},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4480/},
        abstract = {With the development of virtual reality (VR) technology and its applications in many fields, creating simulated hands in the virtual environment is an e ective way to replace the controller as well as to enhance user experience in interactive processes. Therefore, hand tracking problem is gaining a lot of research attention, making an important contribution in recognizing hand postures as well as tracking hand motions for VR?s input or human machine interaction applications. In order to create a markerless real-time hand tracking system suitable for natural human machine interaction, we propose a new method that combines generative and discriminative methods to solve the hand tracking problem using a single RGBD camera. Our system removes the requirement of the user having to wear to color wrist band and robustifies the hand localization even in di cult tracking scenarios.}
}