Estimation and Adaptive Smoothing of Camera Orientations for Video Stabilization and Rolling Shutter Correction

Abstract: Most mobile video-recording devices of today, e.g. cell phones and music players, make use of a Rolling Shutter camera. The camera captures video by recording every frame line-by-line from top to bottom leading to image distortion when either the target or camera is moving. Capturing video by hand also leads to visible frame-to-frame jitter. This thesis presents algorithms for estimation of camera orientations using accelerometer and gyroscope. These estimates can be used to reduce the image distortion caused by camera motion using image processing. In addition an adaptive low pass filtering algorithm used to produce a smooth camera motion is presented. Using the smooth motion the frame-to-frame jitter can be reduced. The algorithms are implemented on the iPod 4 and two output videos are evaluated in a blind experiment with 30 participants. Here, videos are compared to those of competing video stabilization software. The results indicate that the iPod 4 application performs equal or better than its competitors. Also the iPod 4 accelerometer and gyroscope are compared to high end reference sensors in terms of bias and variance.