  We propose an algorithm for recovering depth using less than two images.
Instead of having both cameras send their entire image to the host computer,
the left camera sends its image to the host while the right camera sends only a
fraction $\epsilon$ of its image. The key aspect is that the cameras send the
information without communicating at all. Hence, the required communication
bandwidth is significantly reduced.
  While standard image compression techniques can reduce the communication
bandwidth, this requires additional computational resources on the part of the
encoder (camera). We aim at designing a light weight encoder that only touches
a fraction of the pixels. The burden of decoding is placed on the decoder
(host).
  We show that it is enough for the encoder to transmit a sparse set of pixels.
Using only $1+\epsilon$ images, with $\epsilon$ as little as 2% of the image,
the decoder can compute a depth map. The depth map's accuracy is comparable to
traditional stereo matching algorithms that require both images as input. Using
the depth map and the left image, the right image can be synthesized. No
computations are required at the encoder, and the decoder's runtime is linear
in the images' size.
