Automatic complicated target identification method based on hierarchical object semantic graph

A complex target, automatic recognition technology, applied in the field of target recognition

Inactive Publication Date: 2012-07-04
INST OF ELECTRONICS CHINESE ACAD OF SCI
View PDF3 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a complex target automatic recognition method based on hierarchical object semantic graph to solve the problem of automatic recognition and extraction of complex targets in images

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
  • Automatic complicated target identification method based on hierarchical object semantic graph
  • Automatic complicated target identification method based on hierarchical object semantic graph
  • Automatic complicated target identification method based on hierarchical object semantic graph

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0100] A complex target automatic recognition method based on a hierarchical object semantic graph of the present invention proposes a new hierarchical object semantic graph, which establishes semantic constraints between the target and the background at a high level, and strengthens the relationship between target components at a low level. The geometric constraints between objects, and the mutual influence between object characteristics are calculated through the belief message passing mechanism, and the utilization rate of spatial information in object networks is improved. At the same time, the method adopts a spiral mixed learning method, which crosses the training process of production and discriminative methods to achieve accurate positioning, extraction and recognition of multiple types of complex targets. The present invention overcomes the disadvantages of incomplete description of common features between targets and low utilization rate of high-level semantic informa...

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 an automatic complicated target identification method based on a hierarchical object semantic graph, and relates to a target identification technology. The automatic complicated target identification method comprises the following steps of: establishing a multi-class complicated target image representative set; performing multi-scale partitioning on an image of a training set, gradually calculating characteristic information of each part object, and constructing a hierarchical semantic graph; counting partial characteristic attributes of objects by using a judgment type classifier by adopting a spiral mixed learning mode, calculating interactive influence among the objects by combining a generation type message transmission mechanism, and deducing and calculating the hierarchical semantic graph; and resolving a target of interest in the image by using the hierarchical object semantic graph obtained by learning, and realizing positioning, extraction and type identification of a plurality of classes of complicated targets. The method is relatively high in intelligentization degree; and requirements for identifying a plurality of classes of complicated targetsin natural and remotely sensed scene images and explaining the images can be met.

Description

technical field [0001] The present invention relates to the technical field of target recognition in image information processing, in particular to a complex target automatic recognition method based on a hierarchical object semantic map, which realizes the recognition of various types of complex targets in natural and remote sensing scene images by constructing a hierarchical object semantic map. Target recognition and extraction. Background technique [0002] Object recognition refers to the process of simulating human vision and analysis process, and using computer to perform feature analysis and conceptual understanding of the objects contained in the image scene. Traditional object recognition methods mostly rely on manual or human-computer interaction visual interpretation, which is generally time-consuming and long-term. Improving the automation of target recognition methods can not only liberate people from the boring and complicated image interpretation work, but a...

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): G06K9/66
Inventor 孙显张道兵付琨王宏琦
Owner INST OF ELECTRONICS CHINESE ACAD OF SCI
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