Publication

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Time encoding is a real-time asynchronus mechanism of mapping analog amplitude information into multidimensional time sequences. We investigate the exact representation of analog video streams with a Time Encoding Machine realized with a population of spiking neurons. We also provide an algorithm that perfectly recovers streaming video from the spike trains of the neural population. Finally, we analyze the quality of recovery of a space-time separable video stream encoded with a population of integrate-and-fire neurons and demonstrate that the quality of recovery increases as a function of the population size.

Reference

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@inproceedings{LAP08e,
  author = "A. A. Lazar and E. A. Pnevmatikakis",
  title = "A Video Time Encoding Machine",
  year = 2008,
  booktitle = "IEEE International Conference on Image Processing",
  pages = "717-720",
  month = "Oct",
  keywords = "time encoding, video coding, integrateand-fire neurons, frames, gabor wavelets"
}