Information entropy based viewpoint planning for digitization of 3D objects

In this paper, we present an information entropy based viewpoint planning approach for digitalization of 3D freeform objects. The object is firstly sliced into a number of cross section curves, with each cross-section to be reconstructed by a closed B-spline curve. Then, we propose an improved Bayesian information criterion (BIC) for selecting the control point number of B-spline models. Based on the selected model, we use entropy as the measurement of uncertainty of B-spline model to predict the information gain for each cross section curve. After obtaining the predicted information gain of all the B-spline models, we can map the information gain of these B-spline model into the view space. The viewpoint that contains maximal information gain for the object is then selected as the next best view. Finally, we show our experimental results for the digitization and reconstruction of freedom objects with our view planning method.