Autobiographical memory (AM) has been largely investigated as the ability to recollect specific events that belong to an individual's past. However, how we retrieve real-life routine episodes and how the retrieval of these episodes changes with the passage of time remain unclear. Here, we asked participants to use a wearable camera that automatically captured pictures to record instances during a week of their routine life and implemented a deep neural network-based algorithm to identify picture sequences that represented episodic events. We then asked each participant to return to the lab to retrieve AMs for single episodes cued by the selected pictures 1 week, 2 weeks and 6-14 months after encoding while scalp electroencephalographic (EEG) activity was recorded. We found that participants were more accurate in recognizing pictured scenes depicting their own past than pictured scenes encoded in the lab, and that memory recollection of personally experienced events rapidly decreased with the passing of time. We also found that the retrieval of real-life picture cues elicited a strong and positive 'ERP old/new effect' over frontal regions and that the magnitude of this ERP effect was similar throughout memory tests over time. However, we observed that recognition memory induced a frontal theta power decrease and that this effect was mostly seen when memories were tested after 1 and 2 weeks but not after 6-14 months from encoding. Altogether, we discuss the implications for neuroscientific accounts of episodic retrieval and the potential benefits of developing individual-based AM exploration strategies at the clinical level.