Salient target detection method and system based on based on weakly supervised spatial-temporal cascaded neural network

Abstract

The invention is applicable to the field of video and image identification, and provides a salient target detection method. A spatial-temporal cascaded neural network consists of a first fully convolutional network and a second fully convolutional network. The method comprises the following steps: inputting a current frame of image of a to-be-detected video to the first fully convolutional networkto obtain a spatial prior map; generating a temporal prior map according to the current frame of image and the optical flow map thereof; carrying out element operation on the spatial priori map and the temporal prior map to get a spatial-temporal prior map; and inputting the spatial-temporal priori map and the next frame of image to the second fully convolutional network to get a spatial-temporalsaliency map. According to the embodiments of the invention, in the detection of a salient target in a video with a complex scene, the spatial prior information of the video frame image and the temporal prior information based on the optical flow are integrated to eliminate a static salient region and generate a final spatial-temporal saliency map in a dynamic scene, so that more and richer information can be obtained in the dynamic scene, and the accuracy and robustness are improved.

Description

technical field [0001] The invention belongs to the field of video and image recognition, in particular to a salient target detection method and system based on a weakly supervised space-time cascaded neural network. Background technique [0002] Salient object detection aims to identify relatively attractive objects or regions in images or videos. It has a wide range of applications in object segmentation, object recognition, object tracking and other fields, and is the focus of computer vision research. Salient object detection for static images only considers spatial information, while salient object detection for dynamic videos considers both spatial and temporal information. Therefore, deep learning models for static images are less effective in dynamic video scenes. [0003] How to eliminate the interference of relatively complex background areas in videos is a key issue in salient object detection. Existing saliency detection methods can be divided into two categorie...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a salient object detection method and system based on a weakly supervised spatio-temporal cascaded neural network, aiming to solve the problem that the existing salient detection methods are less accurate and robust in complex scenes. bad question

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