  This work focuses on reducing the computational cost of repeated video
encodes by using a lower resolution clip as a proxy. Features extracted from
the low resolution clip are used to learn an optimal lagrange multiplier for
rate control on the original resolution clip. In addition to reducing the
computational cost and encode time by using lower resolution clips, we also
investigate the use of older, but faster codecs such as H.264 to create
proxies. This work shows that the computational load is reduced by 22 times
using 144p proxies. Our tests are based on the YouTube UGC dataset, hence our
results are based on a practical instance of the adaptive bitrate encoding
problem. Further improvements are possible, by optimising the placement and
sparsity of operating points required for the rate distortion curves.
