(eng): This chapter considers the problem of clustering non-Gaussian data with fixed bounds via recursive mixture estimation under the Bayesian methodology. Here a mixture of uniform distributions is taken, where individual clusters are described by mixture components. The mixture estimation algorithm is based on (i) the update of reproducible statistics of uniform components, (ii) the heuristic initialization via the method of moments, (iii) the non-trivial adaptive forgetting technique, (iv) the data-dependent dynamic pointer model.