Visual saliency-based complex environment face detection method

A face detection and complex environment technology, applied in the field of face detection in complex environments, can solve the problems of unconstrained face detection, such as unsatisfactory results, and achieve the effects of removing image background interference, shortening running time, and reducing computational complexity

Active Publication Date: 2016-08-10
广州棋云信息科技有限公司
View PDF5 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to provide a complex environment face detection method based on visual saliency to solve the problem i

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
  • Visual saliency-based complex environment face detection method
  • Visual saliency-based complex environment face detection method
  • Visual saliency-based complex environment face detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0039] A complex environment face detection method based on visual saliency, the implementation framework is as follows figure 1 shown. First, use the visual attention mechanism to obtain the face saliency map; then segment the saliency map to obtain the binary template; use the morphological operator to adjust the binary template to cover the entire face area; finally match the template with the original image to detect the face target area.

[0040] The specific implementation process of this complex environment face detection method based on visual saliency is as follows: figure 2 shown. The steps are described as follows:

[0041] S1. The input image is a 250×250 grayscale image I(x, y), and the saliency map of the target face area is extracted using the visual saliency map algorithm, which is denoted as S(x, y).

[0042] S2. Use the bicubic interpolation algorithm to adjust the size of the S(x,y) image to the original image size of 250×250, divide each pixel in S(x,y...

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 present invention provides a visual saliency-based complex environment face detection method. According to the invention, a visual attention mechanism is utilized to obtain a face saliency map; the saliency map is segmented, so that a binary template can be obtained; a morphological operator is utilized to adjust the binary template, so as to make the binary template cover an entire face area; and the template is matched with an original image, so that a face target area can be detected out. According to the visual saliency-based complex environment face detection method, the visual attention mechanism is utilized to obtain the face saliency map; the effective face target area is accurately positioned according to the saliency map; and therefore, the influence of factors such as illumination, poses and occlusion in a complex environment can be eliminated, and manual intervention-free, automatic and accurate detection of a non-restraint face target area can be realized.

Description

technical field [0001] The invention relates to a face detection method in a complex environment based on visual saliency. Background technique [0002] Face detection is a key technology in unconstrained face recognition. Accurate detection of face regions in complex backgrounds is crucial for subsequent face recognition work. On the one hand, it can reduce the computational complexity of subsequent work, on the other hand, it can also remove background interference and improve the accuracy of facial features. [0003] At present, the commonly used face detection algorithms mainly include face detection algorithms based on template matching and face detection algorithms based on skin color. The face detection algorithm based on template matching summarizes a unified face template based on the prior data, and then manually selects the position of the human eyes to obtain the distance between the eyes, and uses the face template to detect the face area according to the dista...

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
CPCG06V40/162G06V40/172
Inventor 童莹陈凡曹雪虹
Owner 广州棋云信息科技有限公司
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