Monocular infrared image depth estimation method based on optimized BP (Back Propagation) neural network model

A BP neural network, infrared image technology, applied in the field of monocular infrared image depth estimation based on genetic algorithm optimization of BP neural network model, can solve the problem of inaccurate categories without learning

Inactive Publication Date: 2012-10-24
DONGHUA UNIV
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Although this method is suitable for a series of pictures with simple scenes and achieves the

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  • Monocular infrared image depth estimation method based on optimized BP (Back Propagation) neural network model
  • Monocular infrared image depth estimation method based on optimized BP (Back Propagation) neural network model
  • Monocular infrared image depth estimation method based on optimized BP (Back Propagation) neural network model

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[0031] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0032] Such as figure 1 As shown, the present embodiment discloses a method for estimating the depth of a monocular infrared image based on a BP neural network model optimized by a genetic algorithm, and the steps are as follows:

[0033] Step 1. Obtain any monocular infrared image I(x, y) and the depth map corresponding to the monocular infrared image I(x, y);

[0034] Step 2. Set feature areas on three different scales for ...

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Abstract

The invention relates to a monocular infrared image depth estimation method based on an optimized BP (Back Propagation) neural network model. The method comprises the following steps of: acquiring a monocular infrared image and a depth map to which the monocular infrared image corresponds; setting at least three feature regions with different scales for pixel points in the monocular infrared image; calculating feature vectors of the feature regions to which the pixel points in the monocular infrared image correspond; screening all the feature vectors by successively using stepwise linear regression and independent component analysis methods to obtain feature vectors conforming to depth information of the infrared image; constructing a depth training sample set by using the obtained feature vectors and the depth map to which the infrared image corresponds, and performing nonlinear fitting on the feature vectors in the set and depth values of the depth map by using a BP neuron network, and optimizing the BP neuron network through a genetic algorithm, and then constructing a depth model; and analyzing the monocular infrared image through the depth model to obtain a depth estimated value. By using the monocular infrared image depth estimation method based on the optimized BP neural network model, the depth information of the infrared image can be relatively accurately estimated.

Description

technical field [0001] The invention relates to the technical field of infrared image depth estimation, in particular to a monocular infrared image depth estimation method based on genetic algorithm optimization of BP neural network model. Background technique [0002] Image depth estimation is to obtain depth and distance information from images, which is essentially a problem of depth perception. The spatial position information constructed by depth perception represents the relative distance from the observer to the detected surfaces in the scene. There is an ideal algorithm for restoring the depth and distance information in color images, but for infrared images, because it reflects the temperature distribution of the scene, there are defects such as low signal-to-noise ratio and low contrast, the depth algorithm for restoring the image Still blank. If the depth information of the infrared image can be restored, it will greatly improve the human eye's understanding of ...

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Application Information

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IPC IPC(8): G06T7/00G06N3/08
Inventor 孙韶媛席林
Owner DONGHUA UNIV
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