  This paper studies a new problem, namely active lighting recurrence (ALR)
that physically relocalizes a light source to reproduce the lighting condition
from single reference image for a same scene, which may suffer from
fine-grained changes during twice observations. ALR is of great importance for
fine-grained visual inspection and change detection, because some phenomena or
minute changes can only be clearly observed under particular lighting
conditions. Therefore, effective ALR should be able to online navigate a light
source toward the target pose, which is challenging due to the complexity and
diversity of real-world lighting and imaging processes. To this end, we propose
to use the simple parallel lighting as an analogy model and based on Lambertian
law to compose an instant navigation ball for this purpose. We theoretically
prove the feasibility, i.e., equivalence and convergence, of this ALR approach
for realistic near point light source and small near surface light source.
Besides, we also theoretically prove the invariance of our ALR approach to the
ambiguity of normal and lighting decomposition. The effectiveness and
superiority of the proposed approach have been verified by both extensive
quantitative experiments and challenging real-world tasks on fine-grained
change detection of cultural heritages. We also validate the generality of our
approach to non-Lambertian scenes.
