Three-dimensional reconstruction method of vehicle-borne infrared images

Abstract

The invention discloses a three-dimensional reconstruction technology of vehicle-borne infrared images. The technology mainly adopts an infrared three-dimensional reconstruction technology combining a panel parameter Markov random field PP-MRF model and a superpixel division technology. As an infrared image division technology, the superpixel division technology adopts Law's mask to extract superpixel features in a multiscale condition. A multi-condition training method is introduced to adjust internal parameters of the panel parameter Markov random field PP-MRF model. A trained model is used for estimating panel parameters of each panel of a test image, namely the relative position relation between the panel and a camera. The relative positions between a road and the sky are determined through a method of searching a horizontal line, and finally the three-dimensional reconstruction operation of the vehicle-borne infrared images is performed through deep and structure information. The technology can perform three-dimensional reconstruction on the vehicle-borne infrared images, and ensures that drivers can more visually understand unicolor infrared image and enhance the sensory ability to the environment.

Description

technical field [0001] The invention relates to a three-dimensional reconstruction technology of a vehicle-mounted infrared image. Background technique [0002] With the popularization of vehicle-mounted infrared assisted driving systems in the civilian field, the research work on vehicle-mounted infrared has gradually attracted people's attention. Depth estimation of infrared images has become a research hotspot in recent years. The research on vehicle-mounted infrared 3D reconstruction, based on the depth estimation of infrared images, is of great significance as a new field of vehicle-mounted infrared research. [0003] In recent years, the 3D reconstruction of binocular visible light has gradually matured. Among them, the 3D reconstruction based on the Belief Propagation algorithm is widely used in the field of stereo vision. But relatively speaking, the development of 3D reconstruction of monocular images is relatively late, and the most representative ones are shape-...

AI Technical Summary

Problems solved by technology

[0005] In terms of depth estimation of infrared images, the infrared depth estimation algorithm based on KPCA and BP neural network and the infrared image depth estimation algorithm based on SVM only perform feature extraction between pixels and a certain range of surrounding pixels, without considering the actual Composition relationship between panels, so correct 3D reconstruction of infrared image cannot be performed

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