Optimization algorithm of unmarked flat object recognition

A technology of plane objects and optimization algorithms, applied in character and pattern recognition, calculation, computer parts and other directions, can solve the problems of inability to meet real-time requirements, high cost, and inability to reduce the amount of calculation

Inactive Publication Date: 2014-07-02
FUDAN UNIV +1
View PDF2 Cites 25 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the cost of using SIFT descriptors is high, and only KNN can be used in the matching s

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
  • Optimization algorithm of unmarked flat object recognition
  • Optimization algorithm of unmarked flat object recognition
  • Optimization algorithm of unmarked flat object recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] Use the test video of the author of the baseline algorithm to do multiple comparison experiments. The test video has a total of 499 frames and a resolution of 640*480. The video has all the wide-baseline matching issues and even motion blur issues.

[0066] In order to study the influence degree of the optimization at different stages proposed by the present invention on the results, a total of 6 groups of comparative experiments were done, among which ① is the key point of the screening model in Section 3.2, ② is the key point of screening the target frame in Section 4.1, and ③ is ARANSAC.6 in Section 4.2 Group comparison experiments are: (1) Baseline method; (2) Baseline method + ①; (3) Baseline method + ③; (4) Baseline method + ① + ③; (5) Baseline method + ② + ③; (6) ) Baseline method + ① + ② + ③.

[0067] Table 1 Performance reference table for various aspects of comparative experiments

[0068] Performance\Comparative Experiment Number

(1)

(2) ...

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 belongs to the technical field of statistical pattern recognition and image processing and particularly relates to an optimization algorithm of unmarked flat object recognition. The optimization algorithm comprises the steps of taking local feature key points as features of an unmarked object, and extracting features in initial stages of an off-line training stage and a real-time recognition stage by means of a dichotomy decision algorithm; performing off-line training on the key points through a random Ferns classifier; adopting a random sampling consistency algorithm in the recognition stage to obtain the position and the posture of the object in a real-time frame; adding position and posture information of the target object obtained by calculation to a virtual object, and overlaying position and posture information in an actual scene to complete an augmented reality system. According to the optimization algorithm, two optimizations are performed, namely, weighting screen is performed on the key points in a feature detection stage, and an improved ARANSAC fitting algorithm is adopted to enable interior points in an initial random set to be scaled-up and improve fitting performance in the recognition stage. Compared with a basic line algorithm, performance in all aspects can be improved greatly, and requirements for real-time performance and reliability of the augmented reality system can be met.

Description

technical field [0001] The invention belongs to the technical field of statistical pattern recognition and image processing, and in particular relates to an optimization algorithm for unmarked planar object recognition, which provides a technical basis for augmented reality. Background technique [0002] Augmented reality is a technology that increases users' perception of the real world through the information provided by the computer system, superimposing computer-generated virtual objects, scenes or system prompt information on the real scene, so as to realize the enhancement of reality. The invention uses a computer vision-based target recognition technology to provide a technical basis for augmented reality. The new interactive mode guided by augmented reality technology has broad application prospects. [0003] The key problem of augmented reality is target recognition and positioning, which refers to a technology that checks whether the target object exists in a comp...

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): G06K9/62
Inventor 金城贾琼冯瑞薛向阳
Owner FUDAN 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