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Automatic Video Editing for Sensor-Rich Videos

机译:用于传感器丰富的视频的自动视频编辑

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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.
机译:我们为使用传感器的移动设备提供了一种捕获视频的新框架,例如智能手机,平板电脑等。许多今天的移动设备配备了各种传感器,包括在视频捕获期间很少使用的加速度计,磁力计和陀螺仪。对于超过视频稳定的任何东西。我们证明这些传感器以及通过计算机视觉技术可以从录制的视频中提取的信息,提供了丰富的数据来源,可以利用自动编辑和“清理”捕获的视频。例如,传感器数据可用于识别从视图中隐藏的不期望的视频段。我们展示了一个Android视频录制应用程序,在视频录制过程中捕获传感器数据,并且能够自动从录制的视频构建最终切割。该应用程序使用捕获的传感器数据加上计算机视觉算法,例如聚焦分析,面部检测等,以过滤掉不需要的段,并保持捕获视频的视觉上吸引人的部分以创建最终切割。我们还展示了如何组合各种传感器和计算机视觉例程的信息,以创建不同的最终切割,很少或没有用户输入。

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