  Cameras are the most widely exploited sensor in both robotics and computer
vision communities. Despite their popularity, two dominant attributes (i.e.,
gain and exposure time) have been determined empirically and images are
captured in very passive manner. In this paper, we present an active and
generic camera attribute control scheme using Bayesian optimization. We extend
from our previous work [1] in two aspects. First, we propose a method that
jointly controls camera gain and exposure time. Secondly, to speed up the
Bayesian optimization process, we introduce image synthesis using the camera
response function (CRF). These synthesized images allowed us to diminish the
image acquisition time during the Bayesian optimization phase, substantially
improving overall control performance. The proposed method is validated both in
an indoor and an outdoor environment where light condition rapidly changes.
Supplementary material is available at https://youtu.be/XTYR_Mih3OU .
