Sequence image's automatic splicing method based on three-dimension reconstruction

An automatic stitching and sequence image technology, applied in the field of image processing, can solve the problems of light-weight algorithms that are heavy and cannot handle sequence image distortion well, and achieve the elimination of homography distortion, improvement of automatic stitching quality, and elimination of mirror distortion Effect

Inactive Publication Date: 2017-10-10
TONGJI UNIV
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Problems solved by technology

However, this change makes APAP, a lightweight algorithm, quite cumbersome
More importantly, when the image to be stitched does not

Method used

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  • Sequence image's automatic splicing method based on three-dimension reconstruction
  • Sequence image's automatic splicing method based on three-dimension reconstruction
  • Sequence image's automatic splicing method based on three-dimension reconstruction

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Embodiment

[0050] The purpose of the present invention is to propose a method for automatically mosaicing sequential images based on three-dimensional reconstruction. The method extracts SIFT feature points respectively and establishes a k-d tree for n disordered image sequences, and selects m candidate matching images for each image. , use the RANSAC algorithm to calculate the most likely photographic geometric constraints between the candidate images and form a correct matching image set, and use the SfM algorithm for 3D reconstruction to obtain the best fitting reference plane. Using the Moving DLT method to remove the homography distortion of the input image, and finally using the Bundle Adjustment method to solve the similarity transformation matrix of each image, and finally based on the Multi-band blending algorithm, the automatic stitching of panoramic images is realized.

[0051] A method for automatically mosaicing sequential images based on three-dimensional reconstruction, the...

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Abstract

The invention relates to a sequence image's automatic splicing method based on three-dimension reconstruction. The method comprises the following steps: extracting the scale-invariant feature transform (SIFT) feature points respectively from N inputted images; based on the matching condition of the feature points, selecting m candidate matching images corresponding to each image to structure a candidate matching image set; performing three-dimension reconstruction to the candidate matching image set through the use of the structure from motion (SfM) algorithm to obtain a reflected and projected three-dimension plane; seeking the two-dimension reference plane corresponding to the three-dimension plane and projecting it to a designated two-dimension coordinate plane; seeking the mirror distortion parameter of each image and optimizing the splicing effect between adjacent images. Compared with the prior art, the invention is based on the three-dimension point cloud reconstruction method to restore the three-dimension structure of a photographed object and is able to solve the problems with the sequence image splicing when the images and the photographed object cannot meet the homograph restrain conditions, eliminates the homograph distortion of the inputted images and improves the image splicing quality.

Description

technical field [0001] The invention relates to the field of image processing, in particular to an automatic splicing method of sequential images based on three-dimensional reconstruction. Background technique [0002] Lucas BD, Kanade T published an article titled An iterative image registration technique with an application to stereo vision at the 7th International joint conference on Artificial intelligence in 1981, and proposed the optical flow method (Optical Flow) for image registration. Making optical flow the best algorithm for image registration at the time. This type of optical flow estimation is generally considered to require real-time dense sampling to support. Although the coarse-to-fine sampling method can alleviate this constraint to some extent, the sampling size and estimation speed are still endogenously linked. Brox T, Malik J published an article entitled Large Displacement Optical Flow: Descriptor Matching in Variational MotionEstimation in Volume 33,...

Claims

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Application Information

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IPC IPC(8): G06T3/40G06T5/50G06T7/80G06T17/00
CPCG06T5/50G06T3/4038G06T7/80G06T17/00
Inventor 王志成卫刚
Owner TONGJI UNIV
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