Stereo on a budget
  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. 
Dana Menaker, Shai Avidan
cs.CV