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Human face tracing method

A face position and frame image technology, applied in the field of face tracking, can solve the problems of matrix inversion, difficult inversion operation, poor robustness, etc., and achieve the effect of improving robustness, improving tracking ability, and reducing the amount of calculation.

Inactive Publication Date: 2008-07-16
VIMICRO CORP
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  • Summary
  • Abstract
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  • Claims
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Problems solved by technology

But the commonly used linear discriminant analysis will involve the problem of matrix inversion
However, it is usually difficult to perform inverse operations for high-dimensional sparse matrices, making feature extraction less robust

Method used

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  • Human face tracing method
  • Human face tracing method

Examples

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Embodiment Construction

[0019] In the example below, a rotatable rectangle is used X t = ( x t , y t , s x t , s y t , θ t ) To represent the face position in the tth frame image, where x t and y t Respectively represent the horizontal and vertical coordinates of the center of the face, s x t Indicates the width of the face, s y t Indicates the height of the face, θ t Indicates the rotation angle of the face. However, it should be clear that according to the present invention, the position of a human face can also be represented by using more or less feature quantities.

[0020] Fig. 1 shows the main steps of face tracki...

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Abstract

The invention discloses a face tracking method which is used for tracking the position of a face in a continuous video image sequence. The method comprises the following steps: determining the position of the face in a first frame of image; determining a feature subspace with the first frame of image through the maximum class interval standard; reading the images in the video sequence in turn from a second frame of image; concerning each frame of image being read, determining the position of the face in the current frame of image through the position of the face and the feature subspace of the previous frame of image; and updating the feature subspace at intervals of preset number of frames. The invention adopts the maximum class interval standard, thereby strengthening the robustness of face feature extraction. Simultaneously the invention also adopts an increment learning method for on-line updating of the feature subspace, thereby not only improving tracking effect but also meeting real-time requirements.

Description

technical field [0001] The invention relates to the field of human face tracking, in particular to a method for tracking human face positions in continuous video image sequences. Background technique [0002] Face tracking refers to tracking one or more faces in a continuous sequence of video images. Face tracking has very important applications in many occasions, such as intelligent video surveillance, human-computer interaction, access control and so on. Existing face tracking methods generally use linear discriminant analysis (LDA) to extract face features, and then perform face tracking. However, the commonly used linear discriminant analysis involves the problem of matrix inversion. However, it is usually difficult to perform inverse operations for high-dimensional sparse matrices, which makes feature extraction less robust. When using linear discriminant analysis for face tracking, it is easily affected by factors such as facial expression, posture, and illumination...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/20G06K9/62G06T7/246
Inventor 王磊王浩黄英
Owner VIMICRO CORP
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