Human face detection method

A face detection and face technology, applied in the field of face detection, can solve problems such as limited computing power, and achieve the effects of small memory requirements, fewer memory access times, and satisfying memory space.

Inactive Publication Date: 2009-02-18
SHANGHAI ISVISION INTELLIGENT RECOGNITION TECH
View PDF0 Cites 32 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the computing power of the embedded platform is limited. How to reduce the computing load of face detection at the algorithm level, reduce the number of memory accesses, and reduce storage space, so as to obtain a real-time embedded face detection system has become a top priority.

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
  • Human face detection method
  • Human face detection method
  • Human face detection method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0011] see figure 1 , the face detection method of the present invention mainly comprises the following steps:

[0012] The first step: using a plurality of positive samples and negative samples for sample training in advance to obtain the level of detecting whether each sub-region corresponding to each eigenvalue in the image does not belong to a human face according to each eigenvalue of an image Combined classifier, wherein, each feature value can be obtained by calculating the integral map of the face. In this embodiment, 3000 positive samples and 4000 negative samples are used to establish a training sample library in advance, wherein the positive samples contain human faces. An image sample of an image, the negative sample is an image sample that does not contain a face image, and the size of the positive sample used is the same as that of the negative sample. For example, the sample training process can be as follows:

[0013] a) The process of strong classifier traini...

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

Provided is a face detecting method, first through training positive negative samples, a cascade classifier is obtained to detect whether each subarea corresponding to each eigenvalue does not belong to face component in the image according to the eigenvalue of the image, then the face image to be detected is converted to a face grey chart, which is furthermore converted to a face integral image, then the face integral image is divided into a plurality of sub-integral domains, and then the eigenvalue in the corresponding sub-domain of each sub-integral domain is computed according to the obtained cascade classifier, and based on the computed eigenvalue, the cascade classifier is adopted to detect step by step whether each sub-integral domain does not belong to the face component, to eliminate the sub-integral domains which do not belong to the face component, finally, face repeated are is processed combinedly to determine position and size of the face according to the judgement result. Due to floating point and fixed point operation adopted in the detecting process, detecting speed of the face is effectively advanced, meanwhile appropriative memory is reduced.

Description

technical field [0001] The invention relates to a face detection method. Background technique [0002] At present, face detection has been widely used in the new generation of human-machine interface, video surveillance and content-based retrieval and other fields. With the development of embedded technology and smart devices, the field of face detection applications has gradually emerged the requirements of mobility and outdoor work. However, the computing power of the embedded platform is limited. How to reduce the computing load of face detection at the algorithm level, reduce the number of memory accesses, and reduce storage space, so as to obtain a real-time embedded face detection system has become a top priority. [0003] Therefore, how to provide an effective face detection method with fast running speed and small memory usage has become an urgent problem to be solved by those skilled in the art. Contents of the invention [0004] The purpose of the present inven...

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): G06K9/62A61B5/117A61B5/1171
Inventor 徐淑峰赵峰曾文斌
Owner SHANGHAI ISVISION INTELLIGENT RECOGNITION TECH
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