Image depth estimation method and system

A technology of depth estimation and image depth, applied in the field of image depth estimation methods and systems, can solve the problems of non-dense depth map, low efficiency, low accuracy, etc., to achieve the effect of realizing estimation, high efficiency, and increasing the amount of information

Active Publication Date: 2017-10-20
HUAZHONG UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

[0007] In view of the above defects or improvement needs of the prior art, the present invention provides an image depth estimation method and system, the purpose of which is to construct a depth estimation network, use training samples to train the depth estimation network,

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Embodiment Construction

[0040] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0041] Such as figure 1 As shown, an image depth estimation method includes:

[0042](1) Construct a depth estimation network. The depth estimation network includes: an encoding part, a convolutional connection part, and a decoding part. The deconvolution layer of the decoding part is the same as the last convolutional layer in the convolutional block with the same scale as the encoding part. ...

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Abstract

The invention discloses an image depth estimation method and system. The method is implemented by comprising the steps of establishing a depth estimation network, wherein the depth estimation network comprises a coding part, a convolutional connection part and a decoding part, and a deconvolutional layer of the decoding part is connected with a last convolutional layer in a convolutional block with the same scale as the coding part to form a final deconvolutional layer; selecting two continuous images in sample images and a depth image of one image as training samples, and training the depth estimation network by utilizing the training samples to obtain a trained depth estimation network; collecting a test image, and extracting a current frame image of the test image and a previous frame image of the current frame image; and inputting color channels of the current frame image and the previous frame image to the trained depth estimation network to obtain a depth image of the current frame image. The method is high in efficiency; and the obtained depth image is high in accuracy and high in compactness.

Description

technical field [0001] The invention belongs to the field of computer vision, and more particularly relates to an image depth estimation method and system. Background technique [0002] Image depth estimation is widely used in smart car obstacle avoidance, robot control, car assisted driving, augmented reality and other application fields. Vision-based image depth estimation in road scenes uses computer vision technology to obtain guidance information by processing images captured by cameras. Compared with other guidance techniques, the vision-based method does not need to add other sensor facilities, and it is easy to expand the acquisition equipment. With the increase in the number of vehicles in our country and the increasingly complex road conditions and higher requirements for assisted driving functions, vision-based image depth estimation has also been widely used in intelligent assisted driving. [0003] At present, the depth estimation methods based on computer vis...

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Application Information

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IPC IPC(8): G06T7/50G06N3/04G06N3/08
CPCG06N3/08G06T7/50G06T2207/20084G06T2207/20081G06T2207/20024G06N3/045
Inventor 陶文兵张治国
Owner HUAZHONG UNIV OF SCI & TECH
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