For more than three decades, researchers have worked in the area of face recognition. Despite these efforts, face recognition is not ready yet for real world applications. Ear biometric is a relatively new area of research. There have been few studies conducted using 2-D data (image intensity) and 3-D shape data. Because of the lack of robustness of a single biometric, multimodal biometric have caught the attention of researcher in the area of computer vision. There are several motivations for a multi-modal ear and face biometric. First, the ear and face data can be captured using regular cameras. Second, the data collection for face and ear is nonintrusive. Third, the ear and face are physically close to each other and most of the time acquiring data for ear (face) encounters face (ear) too. Most of the time, these two bio-markers exist in an image or video captured from humans’ head and both are available to a biometric system. Thus, a multi-modal face and ear recognition system is more feasible than a multi-modal face and fingerprint recognition system. Based on the above discussion, we present a multi-modal ear and face biometric system.