Three-dimensional target identification method and system

Abstract

The embodiment of the invention provides a three-dimensional target identification method and system, and the method comprises the steps: for a pixel point in an initial reflection laser image, acquiring projector rays according to the first spatial intersection point and the central point of the speckle projector if it is judged that a first spatial intersection point exists between an infrared camera projection ray corresponding to a pixel point and a target sample; based on the first spatial intersection point, the second spatial intersection point, the projector ray, the virtual plane andthe reference speckle pattern, obtaining an intensity value of the pixel point; obtaining a final object speckle pattern according to the intensity values of the pixel points, and obtaining a synthetic data set according to the final object speckle pattern; and identifying the to-be-identified object by using the neural network to obtain an identification result. According to the embodiment of theinvention, under the condition of less training data, the requirement of large-scale data volume of the deep learning network can be met by generating the synthetic data set, so that the target is identified through the neural network.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a three-dimensional object recognition method and system. Background technique [0002] With the continuous development of depth perception technology and artificial intelligence technology, the monocular structured light depth imaging method based on deep learning network has a strong competitive performance by virtue of its strong learning ability and generalization ability. [0003] For the monocular structured light imaging system, research and practice have proved that the performance of the deep learning network depends on the quality and scale of the training data. Therefore, the monocular structured light depth imaging method based on the deep learning network requires large-scale and high-quality data. Each set of data required for deep learning network training includes: object speckle image, reference speckle image, and parallax ground truth (Ground Truth, GT) ...

AI Technical Summary

Problems solved by technology

[0008] The embodiment of the present invention provides a three-dimensional target recognition method and system, which is used to solve the defect that the neural network cannot be used to identify the target when there is less training data in the prior art, and realize the generation of a synthetic data set. Perform training to identify the object to be identified through the trained neural network

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