  Screen recordings are becoming increasingly important as rich software
artifacts that inform mobile application development processes. However, the
amount of manual effort required to extract information from these graphical
artifacts can hinder resource-constrained mobile developers. This paper
presents Video2Scenario (V2S), an automated tool that processes video
recordings of Android app usages, utilizes neural object detection and image
classification techniques to classify the depicted user actions, and translates
these actions into a replayable scenario. We conducted a comprehensive
evaluation to demonstrate V2S's ability to reproduce recorded scenarios across
a range of devices and a diverse set of usage cases and applications. The
results indicate that, based on its performance with 175 videos depicting 3,534
GUI-based actions, V2S is accurate in reproducing $\approx$89\% of actions from
collected videos.
