author = "Garcia, Danson Evan and Zheng, Kai Wen and Tao, Yi and Liu, Yi and 
                         Mann, Steve",
          affiliation = "{University of Toronto} and {University of Toronto} and 
                         {University of Toronto} and {University of Toronto} and 
                         {University of Toronto}",
                title = "Capturing Pictures from Human Vision Using SSVEP and Lock-in 
            booktitle = "Proceedings...",
                 year = "2020",
               editor = "Musse, Soraia Raupp and Cesar Junior, Roberto Marcondes and 
                         Pelechano, Nuria and Wang, Zhangyang (Atlas)",
         organization = "Conference on Graphics, Patterns and Images, 33. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Signal processing, visual field reconstruction, brain-computer 
                         interfaces (BCI), steady-state visually evoked potential (SSVEP), 
                         lock-in amplifier, pattern recognition.",
             abstract = "We present a novel way of using one's eye to capture an image of 
                         what it {"}sees{"} through the use of steady-state visually-evoked 
                         potentials (SSVEP). Existing methods leveraging response patterns 
                         for SSVEP visual image reconstruction show lossy reconstruction 
                         and have a lengthy scanning process. With our signal acquisition 
                         procedure, data collection requirements are significantly 
                         decreased while still improving the signal clarity. The data for 
                         image reconstruction was collected from the Oz positioned 
                         electrode using a low-cost, wearable electroencephalography (EEG) 
                         device. For image reconstruction, software-defined lock-in 
                         amplifier (LIA) and discrete Fourier transform (DFT) signal 
                         processing methods are analyzed.",
  conference-location = "Virtual",
      conference-year = "Nov. 7-10, 2020",
             language = "en",
           targetfile = "PID6607063.pdf",
        urlaccessdate = "2020, Dec. 04"