Automatic Video Editing for Sensor-Rich Videos

Abstract

We present a new framework for capturing videos using sensor-rich mobile devices, such as smartphones, tablets, etc. Many of today's mobile devices are equipped with a variety of sensors, including accelerometers, magnetometers and gyroscopes, which are rarely used during video capture for anything more than video stabilization. We demonstrate that these sensors, together with the information that can be extracted from the recorded video via computer vision techniques, provide a rich source of data that can be leveraged to automatically edit and "clean up" the captured video. Sensor data, for example, can be used to identify undesirable video segments that are then hidden from view. We showcase an Android video recording app that captures sensor data during video recording and is capable of automatically constructing final-cuts from the recorded video. The app uses the captured sensor data plus computer vision algorithms, such as focus analysis, face detection, etc., to filter out undesirable segments and keep visually appealing portions of the captured video to create a final cut. We also show how information from various sensors and computer vision routines can be combined to create different final cuts with little or no user input.