Moving target detection method based on space-time clustering

A moving target detection and moving target technology, applied in the field of moving target detection, can solve the problems of indistinguishable target distinction, high algorithm complexity, poor anti-noise performance, etc., to ensure algorithm stability, low algorithm complexity, and anti-noise performance The effect of improving the noise performance

Pending Publication Date: 2021-11-19
NANJING UNIV OF SCI & TECH +1
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] In short, the problems existing in the existing technology are: poor anti-noise performance, inability to distinguish different targets, and high algorithm complexity

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
  • Moving target detection method based on space-time clustering
  • Moving target detection method based on space-time clustering
  • Moving target detection method based on space-time clustering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] Such as figure 1 As shown, the present invention is based on the space-time clustering moving target detection method, comprises the following steps:

[0028] (10) Image Feature Point Extraction: Carry out corner detection on the target in the initial frame, and extract image feature points;

[0029] The (10) image feature point extraction step is specifically:

[0030] Perform SURF corner detection on the initial frame image, obtain the initial feature point information of the image, and obtain the SURF feature vector of the feature point, and obtain the vector description of the feature point.

[0031] Using SURF corner detection, extract all feature points of the image and record the feature vectors of the feature points for matching with subsequent image frames. SURF corner is an accelerated version of SIFT. In the corner detection process, the box filter is used to approximate the LOG filter, the integral graph is used to speed up the calculation process, and 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 aims to provide a moving target detection method based on space-time clustering, which can give consideration to calculation speed and detection stability, quickly distinguish a dynamic target and a static target from an image sequence, and track the dynamic target to determine the position of the target in an image. The moving target detection method comprises the following steps: (10) extracting image feature points: carrying out corner detection on a target in an initial frame, and extracting the image feature points; (20) feature point track association: performing tracking detection on the extracted image feature points, and performing track association; (30) track displacement clustering: according to different displacements of background motion and target motion in image coordinates, cutting out motion feature points and background feature points through clustering; and (40) motion feature point spatial clustering: according to spatial differences of different targets in the image, combining feature point tracks on the same target, distinguishing feature point tracks on different targets, and recording the track state of each motion target at the same time.

Description

technical field [0001] The invention belongs to the technical field of moving target detection, and proposes a target extraction algorithm for quickly distinguishing dynamic targets and static targets. Background technique [0002] Moving target detection refers to the ability to identify image changes in a specified area, detect the existence of moving targets and avoid interference caused by light changes. Motion detection such as MPEG1 is to compare and analyze the key frames generated after encoding. The principle is to divide the image sequence into key frames (I), predicted frames (P frames) and double interpolated inward frames (B frames). Process comparisons are performed on the encoded data. Common methods of data processing include: [0003] (1) Background subtraction: Background subtraction is one of the most commonly used methods, which uses the difference between the current image and the background image to detect motion regions. It can generally provide th...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34G06K9/46G06K9/62G06T7/13G06T7/194G06T7/246
CPCG06T7/246G06T7/13G06T7/194G06T2207/20164G06F18/23G06F18/22
Inventor 钱惟贤杨文广高丹陈钱顾国华万敏杰任侃
Owner NANJING UNIV OF SCI & TECH
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