Lifelogging cameras are small and wearable cameras that capture up to 1,500 images per day. Prior work has shown that these images support the episodic recall of not only the memory-impaired patients but also of the general population. However, the sheer volume of the captured image sets exceeds the capability of users to review them on a regular basis. Hence, it would be desirable to automatically detect relevant images in a set of captured images and present them in a way that supports the episodic recall. For that reason, we develop a software that recognizes relevant images and present them in the form of a video summary. Requirements for these video summaries were elicited and evaluated in the context of a five-week study. In this work, we present criteria for relevant images and how they should be presented to benefit the episodic recall. An evaluation of our video summaries revealed that there is no significant difference in the effect on the episodic memory in comparison to review methods that present the entire lifelogging image set. Moreover, participants prefer video summaries over said non-summarizing review methods due to a better usability which can play an important role in elevating this memory augmentation technology from a clinical niche application to a mainstream technology