Human body detection method based on Gauss shape feature

A shape feature, human body detection technology, applied in instruments, computing, character and pattern recognition, etc., can solve problems such as unsatisfactory detection rate and detection speed

Inactive Publication Date: 2009-10-21
HUAZHONG UNIV OF SCI & TECH
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Problems solved by technology

[0003] The invention provides a human body detection method based on Gaussian shape features, which solves the pro

Method used

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  • Human body detection method based on Gauss shape feature
  • Human body detection method based on Gauss shape feature
  • Human body detection method based on Gauss shape feature

Examples

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Example Embodiment

[0084] Combine below figure 1 , figure 2 and Examples describe the present invention in detail.

[0085] This example is based on the French INRIA human dataset (see http: / / lear.inrialpes.fr / data ), the INRIA human body data set includes a positive sample training set containing 2416 images of a human body, an original image training set of 1218 images without a human body, a positive sample test set of 1126 images containing a human body, and 453 The original test set of images without human bodies.

[0086] The 2416 images of the positive sample training set in the INRIA human body dataset are cropped to obtain 2416 images of 70×134 pixels as the positive sample training set, and 2416 images of 70×134 pixels are extracted from the 1218 images of the original image training set images as negative training set.

[0087] The specific implementation steps of this embodiment are as follows:

[0088] Step 1, feature extraction, including the following sub-steps:

[0089] 1...

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Abstract

The invention relates to a human body detection method based on Gauss shape feature, belongs to the field of computer vision and mode identification, and solves the problem that the detection rate and detection speed of the prior detection method are low. The method comprises: a first step of extracting feature, namely extracting the Gauss shape feature of each rectangular area of each training sample; a second step of constructing cascade detectors, namely studying the current training sample to construct the cascade detectors; and a third step of detecting human body, namely using the cascade detectors to scan and detect an image to be detected to determine the position and size of the human body in the image. The method has strong robust property for changes of illumination, background and the like by using the constructed Gauss shape feature, and has low feature dimension; the construction of the Gauss shape feature is added with a mean value of areas so as to enhance the capability of identifying the human body and the background; therefore, the constructed cascade detectors can greatly improve the detection rate of the human body, and can be applied to intelligent monitoring, assistant driving and human-computer interaction systems.

Description

technical field [0001] The invention belongs to the field of computer vision and pattern recognition, and in particular relates to a human body detection method based on Gaussian shape features. Background technique [0002] Human body detection in image recognition is one of the most difficult problems in the field of object detection. The key to human body detection is to design appropriate image features to distinguish human bodies from backgrounds, and to design appropriate learning methods for classification. At present, Haar feature has been successfully applied in face detection, and many researchers have applied it to human body detection. For example, Oren et al. use overlapping Haar features to train Support Vector Machine (SVM) for human body detection, see M .Oren, C.Papageorgiou, P.Sinha, E.Osuna, and T.Poggio.Pedestrian detection using wavelet templates.IEEE Conference on Computer Vision and Pattern Recognition, 1997; Viola et al. extend the Haar feature to des...

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Application Information

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IPC IPC(8): G06K9/00G06K9/66
Inventor 王天江刘芳龚立宇张富强
Owner HUAZHONG UNIV OF SCI & TECH
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