Video shooting anti-shaking method based on mobile apparatus GPU and angular velocity sensor

Abstract

The invention discloses a video shooting anti-shaking method based on a mobile apparatus GPU and an angular velocity sensor. The method comprises following steps: collecting and acquiring angular velocity data through the angular velocity sensor; integrating the collected angular velocity data so as to obtain preliminary prediction information of inter-frame and intra-frame motion directions and angles; further predicting inter-frame motions according to the preliminary prediction information of the inter-frame motion directions and angles so as to obtain final prediction information of the inter-frame motion directions and angles, and giving correction terms back; performing filtering processes according to the preliminary prediction information and the correction terms of the inter-frame motion directions and angles, and giving inter-frame motion compensation items back; and performing rotation transformation on each pixel of each frame image according to the compensation terms and the preliminary prediction information of the inter-frame motion directions and angles, removing rolling shutter effects and performing motion compensation so as to obtain final frame images. By employing the method, the rolling shutter effects can be removed, motion compensation is achieved, burdens of the GPU are reduced, and excellent video anti-shaking effects are achieved.

Description

technical field [0001] The present invention relates to video processing, in particular to a video shooting anti-shake method based on a mobile device GPU and an angular velocity sensor. Background technique [0002] At this stage, many mobile devices such as mobile phones or tablets can support real-time anti-shake processing during video shooting. The most common anti-shake method is to adopt optical anti-shake or digital anti-shake based on image processing. The use of optical image stabilization method requires the hardware support of the device, which can only be realized on a few relatively high-end mobile devices. Digital image stabilization is generally implemented by predicting inter-frame motion and then implementing compensation. Among them, inter-frame motion prediction requires a relatively large amount of calculation, and generally needs to be realized by GPU or a dedicated DSP. However, the direction and degree of shaking during handheld photography are ever...

AI Technical Summary

Problems solved by technology

Among them, inter-frame motion prediction requires a relatively large amount of calculation, and generally needs to be realized by GPU or a dedicated DSP. However, the direction and degree of shaking during handheld photography are ever-changing. To implement accurate inter-frame motion prediction requires a relatively large amount of search, and Ineffective against in-frame jelly effects caused by rolling shutter

At the same time, the angular velocity sensors on many mobile devices generally use low-cost devices with relatively low accuracy, which is not suitable for continuous integration to calculate the motion angle

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