Abstract: Event cameras offer benefits in High Temporal Resolution (HTR), High Dynamic Range (HDR), and minimal motion blur, but only image moving scenes and do not measure absolute intensity. Conversely, frame based cameras are ideally suited to imaging static scenes and measuring absolute intensity, but are prone to image blur and have low temporal resolution. Hybrid sensors such as the Dynamic and Active Pixel Vision Sensor (DAVIS), and other custom built or commercial systems, combine event and frame based sensing at the pixel level allowing fusion of these two complementary sensor modalities to provide enhanced imaging. However, the circuitry required to register both visual modalities at the individual pixel level for a mono hybrid event-frame camera tends to compromise the performance of each separate sensor modality. An alternative is to consider Stereo Hybrid Event-Frame (SHEF) camera systems with separate event and frame sensor systems. Such systems allow the fusion of high quality event data with high quality frame based data but require the registration problem to solved, that is, the question of computing the disparity between asynchronous events and synchronous frames. In this talk I discuss this question and introduce a first baseline solution.