Motion Vector Estimation of Textureless Objects Exploiting Reaction-Diffusion Cellular Automata

It is difficult to detect motion vectors for textureless objects, because variations in brightness are needed for motion vector estimation. To solve this problem, we proposed a reaction-diffusion (RD) texture generation algorithm. The RD model is a well-known method of spatial pattern generation. Using RD, we were able to generate texture on textureless objects. In our research, we have tried to generate texture on objects by processing the two-dimensional RD. However, this poses the problem of suppressing noise diffusion. Therefore, in this study, we attempt to inhibit noise diffusion by processing the onedimensional RD model.