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Foreground target key frame processing-based video abstract generation method

A video summary and key frame technology, applied in the field of image processing, can solve the problem that users cannot effectively and quickly browse surveillance video

Active Publication Date: 2018-04-20
JIANGSU UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the defect in the existing technology that the user cannot effectively and quickly browse the surveillance video, the present invention provides a method for generating video summaries based on the key frame of the foreground target

Method used

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  • Foreground target key frame processing-based video abstract generation method

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Embodiment Construction

[0059] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0060] A kind of foreground object keyframe video summarization generation method of the present embodiment, such as figure 1 As shown, the specific process of its generation method is as follows:

[0061] S101. Construct a training data set containing foreground objects to be detected in the target video, and perform training through the SSD network until optimal SSD network parameters are obtained.

[0062] In the specific implementation, taking the traffic road as an example, the images mainly of vehicles and pedestrians are collected, the collected images are classified, and the training samples are selected to form the training data set of the SSD network.

[0063] Use the data set to train the SSD network, and adjust the network parameters according to the intermediate training results until the network training converges to complete the training...

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Abstract

The invention discloses a foreground target key frame processing-based video abstract generation method and belongs to the field of image processing. The method comprises the steps of performing detection on an image by utilizing a target classifier trained by a convolutional neural network frame by frame for a to-be-processed video stream; in combination with a tracking algorithm, tracking a foreground target of each frame, and performing gradual updating to obtain a target motion track; deleting foreground targets in a video to obtain a video background without motion targets; for an extracted foreground target sequence, removing similar elements to form a foreground target sequence after key processing; and fitting an extracted target image fusion algorithm to a background image, displaying related information, and concentrating the whole video stream into a small amount of video frames to form a video summary. A deep learning technology is used for performing target detection and is combined with the tracking algorithm, so that foreground target detection and tracking are efficiently realized and interference of scene noises on video processing is reduced; the video is re-rendered by an independent target, and time-space data is compressed, so that the video browsing rate is increased; and the method is applied to complex scenes.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to a method for generating video summaries with key-framed foreground objects. Background technique [0002] Surveillance video is generally recorded by a fixed camera 24 hours a day. According to reports, less than 1% of the massive video information may really play a role. Our country invests a huge amount of money to build the monitoring system and the benefits are very small. Facing such massive video information, the most urgent problem to be solved is how to improve browsing efficiency so as to make full use of video information. Improve the acquisition and processing speed of video events, and reduce the omissions of manual video processing efficiency. [0003] Video data has the characteristics of strong expressiveness and vivid images, but its huge data volume, opaque content, and unstructured data make it very inconvenient to organize, manage, and analyze video data. In...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06T5/50G06T7/194G06T7/246
CPCG06F16/739G06T5/50G06T7/194G06T7/246G06T2207/10016G06T2207/20221
Inventor 朱洪锦邰阳范洪辉叶飞跃
Owner JIANGSU UNIV OF TECH
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