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Human face detection method based on picture geometry

A geometric structure and face detection technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as poor performance, affecting the performance of the final cascade classifier, and not reflecting the contrast between long-distance macroblocks. To achieve the effect of low calculation

Inactive Publication Date: 2008-08-06
TSINGHUA UNIV
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Problems solved by technology

[0008] However, even though the edge description range of Haar-like features is wider, they still cannot reflect the contrast between distant macroblocks, so they are still a local feature
And the weak classifier used is the simplest decision tree with poor performance, which affects the performance of the final cascade classifier

Method used

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  • Human face detection method based on picture geometry
  • Human face detection method based on picture geometry
  • Human face detection method based on picture geometry

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Embodiment Construction

[0051] Specific embodiments of the present invention are described below in conjunction with accompanying drawing:

[0052] Face detection ideas based on image geometry: When people recognize objects, they often use a method based on component structure to describe them naturally. For example, a human face is formed by a regular arrangement of a nose, two eyes, and a mouth. The facial features are always darker than the rest of the skin. The difference relationship between macroblocks is used to describe the contrast relationship between components, and the resulting feature is called the geometric structure of the picture.

[0053] The first step of the present invention normalizes the face samples, the second step extracts the geometric structure of the picture as a feature, and the third step uses the feature training waterfall cascade classifier, and its kernel weak classifier adopts a support vector machine (SVM) Classifier. The final classifier is a calculation in the f...

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Abstract

The invention discloses a face detection method based on a picture geometric structure, comprising a training process of face models and a detecting process of face images. The method comprises the following: the step of the training process of face models is divided into a step of training sample normalization, a step of feature extraction, a partitioning step of dividing a sample by adopting a block with a proper size, a step of drawing all differential values acquired by operations into a feature column vector to submit to a classifier for learning, a learning process of a fall type support vector machine and a classification against a sample picture in each window by using a cascade classifier; and the step of the detection of face images is to mark a detected face. The face detection method solves the problem generally existed in the field that the prior art aims at the local structure of a picture but can not completely and accurately express global information of the picture, and can detect a face quickly and accurately.

Description

technical field [0001] The invention relates to a face detection method based on the geometric structure of pictures, which belongs to one of the key technologies in the fields of computer vision and video intelligent monitoring. Background technique [0002] In the field of computer vision and video intelligent surveillance, face detection has become a very important and cutting-edge research topic. Precisely locating faces can provide authentication, capture and tracking of people, etc., and is one of the basic algorithms in intelligent surveillance. The new generation of digital cameras already have real-time face detection for face priority focusing. The research and development of face detection mainly focus on the improvement of two aspects: detection accuracy and detection speed. [0003] Face detection is the most practical achievement in the field of target detection. Its core algorithm generally uses a pattern recognition method based on supervised learning. Firs...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00
Inventor 曹子晟陈峰张伟东
Owner TSINGHUA UNIV
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