Within our ongoing effort to develop a computational model to understand multi-modal human dialogue in the field of elderly care, this paper focuses on pronominal and deictic co-reference resolution. After describing our data collection effort, we discuss our annotation scheme. We developed a co-reference model that employs both a simple notion of markable type, and multiple statistical models. Our results show that knowing the type of the markable, and the presence of simultaneous pointing gestures improve co-reference resolution for personal and deictic pronouns.