Convolution theorem based face verification accelerating method

A convolution theorem and face verification technology, applied in the field of face verification in computer vision, can solve the problems of large computational burden and slow running speed of the face verification system

Active Publication Date: 2017-05-24
深圳市小枫科技有限公司
View PDF4 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems of large computational burden and slow running speed of the face verification system, the purpose o

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
  • Convolution theorem based face verification accelerating method
  • Convolution theorem based face verification accelerating method
  • Convolution theorem based face verification accelerating method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0054] Hereinafter, the present invention will be further described in detail with reference to the drawings and embodiments. In the present invention, GPU is used as the computing platform, CUDA is used as the GPU parallel computing framework, and Caffe is selected as the CNN framework.

[0055] The specific implementation steps are as follows:

[0056] Step 1: Determine whether the acceleration condition is met by the input parameters of the convolutional layer.

[0057] When both K and L are greater than 100 or P is greater than 5, this method can achieve an acceleration effect.

[0058] Step 2: Input image and convolution kernel size expansion.

[0059] CUDA_KERNEL_LOOP parallel loop is used to create N threads, each thread processes the expansion operation of one pixel in the image, and N threads perform the expansion operation in parallel.

[0060] Expanding the size of the input image and the convolution kernel requires additional buffer space. The parameters of each convolution...

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 relates to a convolution theorem based face verification accelerating method, and belongs to the field of face verification in computer vision. For a face verification system adopting a CNN (Convolutional Neural Network) technology, a convolution theorem method is adopted to replace the conventional convolution computation method to perform convolution computation on a convolution layer meeting an acceleration condition on the basis of using a GPU parallel computation platform. The convolution theorem shows that convolution in the space domain is equivalent to product in the frequency domain. Through transforming time-consuming convolution computation into product computation in the frequency domain, the computation amount can be significantly reduced, and the computation speed of a CNN is accelerated. In allusion to problems of great computational burden and slow operation speed of the face verification system, the method enables the operation speed of the face verification system to be obviously improved, and the processing capacity for mass data can be improved.

Description

Technical field [0001] The invention belongs to the field of face verification in computer vision, and relates to an acceleration method for face verification, in particular to a face verification acceleration method based on the convolution theorem. Background technique [0002] With the development of society, people’s requirements for security and convenience are increasing. Face verification technology has made great progress in recent decades. It has the advantages of directness, friendliness, and convenience. It can be used in login verification and identity verification. Recognition and many other scenes have received extensive attention and research. The goal of face verification is to determine whether the faces in two face pictures are the same person, which is mainly composed of three parts: face image preprocessing, feature extraction, and feature measurement. After deep learning was proposed, especially after the application of convolutional neural networks (CNN) in...

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): G06K9/00
CPCG06V40/16
Inventor 刘波郭申
Owner 深圳市小枫科技有限公司
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