In this paper, we introduce a Hybrid Hidden Markov Model (HMM) face recognition system. The proposed system contains a low-complexity 2-D HMM-based face recognition (LC 2D-HMM FR) module that carries out a complete search in the compressed-domain followed by a 1-D HMM-based face recognition (1D-HMM FR) module which refines the search based on a candidate list provided by the first module. We also examine a remote database search methodology that may be helpful for accessing remote resources, where no prior information is assumed regarding the contents of the remote database. The performance of the Hybrid HMM face recognition system is reported for both, local and remote database search modes.