Reflectance Transformation Imaging (RTI) is a computational photographic method that captures an object’s surface shape & color and enables the interactive re-lighting of the subject from any direction. RTI model of an object is built from multiple images of it captured by a stationary camera but varying light directions. By changing the direction of the light, the respective micro-geometry of the object is highlighted. The RTI acquisition process is often long, and tedious when it is not automated. It requires expertise to define for each analysed object which are the number and the relevant lighting positions in the acquisition sequence. In this paper, we present our novel Next Best Light Position (NBLP) method to address this issue. The proposed method is based on the principle of a gradient descent allowing in an adaptive and iterative way, to automatically define the most appropriate lighting directions for the RTI acquisition of an object/surface.