Video Saliency Detection Method Based on Integrated Prediction and Spatiotemporal Domain Propagation

Abstract

The invention discloses a video saliency detection method based on integrated prediction and time-space domain propagation. (1) For the current frame of the video, construct a local temporal window centered on the current frame; (2) Use the optical flow algorithm to calculate the required optical flow field (motion vector field); then perform superpixel segmentation; finally Extract regional features; (3), use the information of the first two frames of the current frame (including the corresponding saliency map), obtain an integrated saliency prediction model, and perform saliency prediction on the current frame; (4), use the first two frames The information is propagated in the forward time domain of the current frame; the information of the first two frames is used to act on the last two frames of the current frame to obtain the corresponding rough spatio-temporal saliency map, and based on this, the current frame is propagated backward in the time domain; (5) , Spatial domain propagation to obtain the spatio-temporal saliency map corresponding to the current frame. The results of this method on unconstrained videos show that it can uniformly light up, highlight salient moving objects, and effectively suppress the background.

Description

technical field [0001] The invention relates to the technical field of image and video processing, in particular to a video saliency detection method based on integrated prediction and time-space domain propagation. Background technique [0002] With the popularization of wearable devices, smart phones and tablet computers with camera and video recording functions, the acquisition and storage of video information has become easier and easier. A large number of unconstrained videos also brings new challenges to research fields such as image and video processing. In recent years, studies have shown that the human visual system can quickly locate the most eye-catching objects from complex scenes, and how to use computer technology to simulate the human eye's visual mechanism and use it to extract human eye interest areas in images and videos has also become a current issue. Research hotspot. In the past few decades, researchers have proposed numerous saliency models and applie...

AI Technical Summary

Problems solved by technology

The motion saliency measure used in this algorithm is used as the initial saliency map, but it often fails for unconstrained videos such as complex scenes

In summary, the existing spatio-temporal saliency models cannot effectively highlight salient moving objects and suppress backgrounds, especially for unconstrained videos, which also hinders the widespread application of video saliency detection methods.

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