In this paper the problem of music performer verification is introduced. Given a certain performance of a musical piece and a set of candidate pianists the task is to examine whether or not a particular pianist is the actual performer. A database of 22 pianists playing pieces by F. Chopin in a computer-controlled piano is used in the presented experiments. An appropriate set of features that captures the idiosyncrasies of music performers is proposed. Well-known machine learning techniques for constructing learning ensembles are applied and remarkable results are described in verifying the actual pianist, a very difficult task even for human experts.