  This paper introduces a live object recognition system that serves as a blind
aid. Visually impaired people heavily rely on their other senses such as touch
and auditory signals for understanding the environment around them. The act of
knowing what object is in front of the blind person without touching it (by
hand or some other tool) is very difficult. In some cases, the physical contact
between the person and object can be dangerous, and even lethal.
  This project employs a Convolutional Neural Network for recognition of
pre-trained objects on the ImageNet dataset. A camera, aligned with the
system's predetermined orientation serves as input to the computer system,
which has the object recognition Neural Network deployed to carry out real-time
object detection. Output from the network can then be parsed to present to the
visually impaired person either in the form of audio or Braille text.
