A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle

A specific target and smart car technology, applied in image data processing, instruments, calculations, etc., can solve the problems of complex topological feature extraction, complex extraction methods, and large amount of calculation, so as to reduce the interference of light and background noise and avoid extraction Effects of inaccuracy, good real-time and robustness

Active Publication Date: 2018-12-11
NANJING UNIV OF POSTS & TELECOMM
View PDF2 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The extraction methods of these three kinds of invariant features are relatively complicated, and the amount of calculation is relatively large, especially the

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
  • A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle
  • A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle
  • A method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicle

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0038] Step 1) Given a target operation domain O and evenly dividing it into A areas of the same size, dispatch A smart car to search from the A areas, and the target existence probability of each area is P i,g,k , i=1,2...A, the k represents the current time, i represents the number of the car, g=g(m,n) represents one of the areas (the (m,n) represents the center coordinates of the area );

[0039] Step 2) Input the target image to be identified, and perform thresholding processing on the gray level to obtain its two-dimensional digital grayscale image f(M, N). Its MN pixels are MN particles on the XOY plane, and denote The centroid coordinates (cx, cy) of the image, and the gray value of each pixel point (x, y) is f(x, y) to indicate the quality of the corresponding particle point; the normalized rotation vector (NMI) method is used to carry out the target detection. Identification and tracking, the specific steps are as follows:

[0040] Step 2.1) Calculate the moment of ...

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 discloses a method for realizing cooperative searching to identify and track a specific target group by multi-intelligent vehicles. The method includes: firstly, a target operation fieldO is initialized and divided into A small blocks, and A intelligent vehicles are used for searching in the A regions. then, by calculating the normalized rotation vector (NMI) of one of the targets in the target group, and the intelligent vehicle continuously collects and preprocesses the images in the search process; the NMI value of the captured image is matched with the input value in advance,if the NMI value is equal, the measurement result is true, otherwise, the target is not found; The measured values are then used as inputs to a single smart car i and the maps are updated separatelyaccording to the Bayesian rules. The nonlinear transformation of a probability graph is introduced to simplify the computation by linearized Bayesian updating. Finally, a distributed fusion scheme similar to consensus is provided, which is applied to map fusion of multi-vehicle, and a new dispersion probability graph is obtained.

Description

technical field [0001] The invention relates to a method for realizing collaborative search, identification and tracking of a specific target group by multiple smart cars, which mainly utilizes a distributed search algorithm, wireless sensor communication technology and a method of extracting normalized rotation vector features to quickly identify and track a large area. Tracking a specific target group belongs to the field of wireless sensor networks, mathematical methods and digital image processing. Background technique [0002] The problem of target search recognition and tracking has always been a very active part of the research field, and it has a very wide range of applications in the military field, intelligent transportation, security defense and other fields. In terms of cooperative control of multiple agents, the current typical research mainly includes cooperative reconnaissance, cooperative search, cooperative target tracking, cooperative positioning and format...

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): G06T7/292G06T5/00
CPCG06T5/002G06T2207/20221G06T7/292
Inventor 陈志狄小娟岳文静汪皓平龚凯
Owner NANJING UNIV OF POSTS & TELECOMM
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