Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Image sample set quality evaluation method and device and storage medium

An image sample set and quality technology, applied in the field of face recognition, can solve the problems of lack of evaluation indicators, difficult face recognition model quality evaluation, low efficiency of human evaluation, etc., to solve the low efficiency of human evaluation and improve efficiency.

Pending Publication Date: 2022-06-21
BEIJING ACADEMY OF AGRICULTURE & FORESTRY SCIENCES
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present disclosure provide a quality assessment method, device, and storage medium for an image sample set, to at least solve the problems existing in the prior art that are difficult to train security checkers due to lack of assessment indicators and low efficiency of human assessment. Technical Issues in Quality Assessment of Image Sample Sets for Face Recognition Models

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
  • Image sample set quality evaluation method and device and storage medium
  • Image sample set quality evaluation method and device and storage medium
  • Image sample set quality evaluation method and device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0027] According to this embodiment, a method embodiment of a method for evaluating the quality of an image sample set is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings may be executed in a computer system such as a set of computer-executable instructions and, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that herein.

[0028] The method embodiments provided in this embodiment may be executed in a mobile terminal, a computer terminal, a server, or a similar computing device. figure 1 A block diagram of the hardware structure of a computing device for implementing a method for evaluating the quality of an image sample set is shown. like figure 1 As shown, a computing device may include one or more processors (the processors may include, but are not limited to, processing means such as a microprocessor MCU or a programmable logic device ...

Embodiment 2

[0192] Figure 11 The quality evaluation device 1100 of the image sample set for training a face recognition model according to this embodiment is shown, and the device 1100 corresponds to the method according to the first aspect of Embodiment 1, wherein the face The recognition model is used in a security screening facility, and the image sample set includes a plurality of face sample images used to train the face recognition model. refer to Figure 11 As shown, the apparatus 1100 includes: a first parameter evaluation module 1110, configured to determine the face sampling quality associated with the face object in the face sample image, and determine the first evaluation of the image sample set according to the face sampling quality parameters; the second parameter evaluation module 1120 is used to determine the second evaluation parameter of the image sample set according to the distribution of face sample images among different categories of persons; the third parameter ...

Embodiment 3

[0207] Figure 12 The quality evaluation device 1200 for training the image sample set of the face recognition model according to the present embodiment is shown, and the device 1200 corresponds to the method according to the first aspect of the embodiment 1, wherein the human face The recognition model is used in a security screening facility, and the image sample set includes a plurality of face sample images used to train the face recognition model. refer to Figure 12 As shown, the apparatus 1200 includes: a processor; and a memory, connected to the processor, for providing the processor with instructions for processing the following processing steps: determining a face object associated with a face sample image face sampling quality, and determine the first evaluation parameter of the image sample set according to the face sampling quality; determine the second evaluation parameter of the image sample set according to the distribution of face sample images among differe...

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 quality evaluation method and device of an image sample set and a storage medium. The method comprises the following steps: determining face sampling quality associated with a face target in a face sample image, and determining a first evaluation parameter of an image sample set according to the face sampling quality; determining a second evaluation parameter of the image sample set according to the distribution of the face sample images among different personnel categories; according to the number of effective sample images in the image sample set, a third evaluation parameter of the image sample set is determined, and the effective sample images are face sample images suitable for determining categories through a deep learning-based model; and evaluating the quality of the image sample set according to the first evaluation parameter, the second evaluation parameter and the third evaluation parameter.

Description

technical field [0001] The present application relates to the technical field of face recognition, and in particular, to a quality assessment method, device and storage medium for an image sample set. Background technique [0002] Face recognition technology needs to train a face recognition model based on deep learning through a large number of face sample images in the image sample set. For a face recognition model, the quality of the face sample images plays a decisive role in the accuracy of the trained face recognition model. Therefore, it is necessary to provide a quality assessment method that can assess the quality of the image sample set, so that people can evaluate the quality of the image sample set used for training the face recognition model, so as to exclude the problem before training the face recognition model. A sample set of images of poor quality. [0003] In addition, the face recognition model can be applied to different application scenarios. And the...

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): G06V40/16G06V40/40G06V10/774G06V10/762G06V10/764G06V10/82G06K9/62G06N3/04G06N3/08G07C9/37
CPCG06N3/08G07C9/37G06N3/045G06F18/23213G06F18/2415G06F18/214
Inventor 李新荣杨金凤田壮何文天宋大平
Owner BEIJING ACADEMY OF AGRICULTURE & FORESTRY SCIENCES
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
Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com