MS-KCF (MobileNet-SSD-kernelized correlation filters) based rapid and stable detection method of human face in image sequence

An image sequence and stable detection technology, applied in image enhancement, image analysis, image data processing, etc., can solve problems such as large angle changes and occluded faces

Active Publication Date: 2018-06-29
SOUTHWEAT UNIV OF SCI & TECH
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Problems solved by technology

This model not only solves the stability problem of face detection with large angle changes and se

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  • MS-KCF (MobileNet-SSD-kernelized correlation filters) based rapid and stable detection method of human face in image sequence
  • MS-KCF (MobileNet-SSD-kernelized correlation filters) based rapid and stable detection method of human face in image sequence
  • MS-KCF (MobileNet-SSD-kernelized correlation filters) based rapid and stable detection method of human face in image sequence

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[0019] The MS-KCF-based fast and stable face detection method in image sequences of the present invention will be further described in detail below with examples and accompanying drawings.

[0020] like figure 1 As shown, it is an overall flow chart of the system of the present invention, including an image sequence acquisition module, an MS detection network module, a KCF tracking module, and a model updating module. As a result, the entire network forms a new automatic detection-tracking-detection (Detection-Tracking-Detection, DTD) cycle update mode, that is, the MS-KCF face detection model.

[0021] Step 1, build MS (MobileNet-SSD) detection network. like figure 2 As shown, the MS detection network structure includes four parts: the first part is the input layer, which is used to input pictures; the second part is an improved MobileNet convolutional network, which is used to extract the features of input pictures; the third part is the SSD metastructure, It is used for...

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Abstract

The invention provides an MS-KCF (MobileNet-SSD-kernelized correlation filters) based rapid and stable detection method of a human face in an image sequence. To solve the problem about detection of the human face with larger angle change and very severe shielding in the image sequence, a new automatic DTD (detection-tracking-detection) mode integrating rapid and accurate target detection model MSand rapid tracking model KCF is provided, that is, an MS-KCF human face detection model is provided. The method comprises steps as follows: S1, establishing an MS detection network; S2, detecting a target by use of the MS network; S3, updating the tracking model to predict the position of the next frame of human face target; S4, updating an MS detection network after tracking several frames, and performing redetection and positioning on the human face target; S5, comparing and analyzing experiment results. Experiments prove that the MS-KFC model guarantees the detection stability of the humanface with larger angle change and very severe shielding in the image sequence, and besides, the detection speed is greatly increased.

Description

technical field [0001] The invention belongs to the technical field of machine vision target detection, in particular to a fast and stable face detection method based on MS-KCF in image sequences. Background technique [0002] With the continuous development of computer technology and the continuous improvement of computer performance, face detection technology, as an important branch in the field of computer vision, has also made great breakthroughs. Today, face detection has a wide range of applications in access control systems, intelligent monitoring, and intelligent cameras. Applications. Face detection is also a challenging technology. How to detect faces with large angle changes and serious occlusions in image sequences in real time and stably has become an urgent problem to be solved in applications. At present, the traditional method of using shallow features can no longer meet the needs, so the deep convolutional neural network (Convolutional Neural Network, CNN) ...

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Application Information

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IPC IPC(8): G06K9/00G06T7/207
CPCG06T7/207G06T2207/20081G06T2207/20084G06T2207/30201G06V40/161
Inventor 李小霞李旻择叶远征
Owner SOUTHWEAT UNIV OF SCI & TECH
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