Monitoring video compression and reconstruction method based on visual attention mechanism

A visual attention mechanism and video monitoring technology, applied in digital video signal modification, electrical components, image communication, etc., can solve the problem of poor reconstructed image quality, improve compressibility, reduce bandwidth and storage memory limitations, The effect of increasing sparsity

Active Publication Date: 2018-07-31
DONGHUA UNIV
View PDF6 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Many of the above methods improve the degree of compression by reducing spatial redundancy or temporal redundancy information. Although they can significantly improve the degree of video compression and

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Monitoring video compression and reconstruction method based on visual attention mechanism
  • Monitoring video compression and reconstruction method based on visual attention mechanism
  • Monitoring video compression and reconstruction method based on visual attention mechanism

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0044] A surveillance video compression and reconstruction method based on visual attention mechanism, such as figure 1 As shown, the specific steps are as follows:

[0045] (1) Divide every 10 consecutive frames of surveillance video into a group to form multiple video frame groups. In each video frame group, determine a video frame as a key frame, the rest of the video frames are non-key frames, and the key frames are each A specified frame in the video frame group or based on image content, cluster extraction, motion analysis, or shot boundary extraction;

[0046] (2) Combining the visual attention mechanism and using the background difference method to extract the moving foreground, each video frame is divided into blocks, that is, the video frame is divided into 32×32 video frame blocks, and then the ROI area is determined according to the moving foreground, the video frame The area outside the area of ​​interest is the non-interest area. The specific steps for determining the...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a monitoring video compression and reconstruction method based on a visual attention mechanism. The method comprises the following steps: dividing a monitoring video into multiple video frame groups, wherein each video frame group determines a key frame; determining an interested region in each video; compressing and reconstructing the key frame and the non-key frame, wherein the step of compressing and reconstructing the non-key frame comprises steps of obtaining image residual obtained by subtracting pixel values of the non-key frame and the corresponding reconstructed key frame, performing blocked compression of different degrees according to the interested region and the non-interested region, reconstructing the compressed blocks of the image residuals at different regions by using different algorithms, and then adding the reconstructed compressed block with the corresponding reconstructed key frame to obtain the reconstructed non-key frame; and finally arranging and reconstructing the reconstructed key frame and the reconstructed non-key frame according to the order before reconstruction, thereby obtaining the monitoring video. The monitoring video iscompressed in different measurement ratio based on the residual application visual attention mechanism blocking, the reconstruction effect is guaranteed, and the compression ratio is reduced.

Description

Technical field [0001] The invention relates to the field of video compression and reconstruction, in particular to a monitoring video compression and reconstruction method based on a visual attention mechanism. Background technique [0002] Visual information is accurate, intuitive, vivid, efficient, widely available and large in capacity. At present, the processing of visual images is mainly static processing. Video analysis and processing technology includes processing of a certain frame of static image and processing of related multi-frame images. [0003] Video technology has been widely used in all walks of life, and video surveillance is one of the most important aspects. A series of surveillance video-based target detection and tracking, motion segmentation and recognition, face recognition and anomaly detection have been continuously developed and practically applied, and they are widely used in traffic monitoring and management, security and wireless sensing systems. Wi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): H04N19/167H04N19/583
CPCH04N19/167H04N19/583
Inventor 郝矿荣杨文峰唐雪嵩韩韬丁永生
Owner DONGHUA UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap