Characteristic point optimization method for three-dimensional reconstruction of video scene
A technology for video scene and 3D reconstruction, applied in 3D modeling, image data processing, instruments, etc., can solve problems such as poor accuracy, and achieve the effect of improving accuracy
Active Publication Date: 2011-02-16
日照新睿招商发展有限公司
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[0005] In order to overcome the shortcomings of the poor accuracy of the existing KLT feature point tracking method for 3D reconstruction of video scenes, the present invention provides a feature point optimization method for effectively improving the accuracy of 3D reconstruction of video scenes
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[0037] The present invention will be further described below in conjunction with the accompanying drawings.
[0038] refer to Figure 1 ~ Figure 3 A method for selecting feature points during three-dimensional reconstruction of a video scene, comprising the following steps:
[0039] 1) Image sequence I(X, t ), where X represents the position of the i-th feature point, and the coordinates of X are ( , ), t Indicates the ordinal number of the frame, using the KLT tracker to track the feature points, setting the time interval between two frames of data in the image sequence to be limited and small, the feature points only change in position, and the brightness remains unchanged, as follows:
[0040] (1)
[0041] in, Represents the brightness of the feature point, X represents the position of the feature point, δ(X) represents the transformation function, Represents a time interval:
[0042] δ( x ) Approximately represented by a vec...
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The invention relates to a characteristic point optimization method for the three-dimensional reconstruction of a video scene, comprising the following steps: 1) in an image sequence I (X, t) of the video scene, X represents the position of the ith characteristic point, t represents the ordinal number of frames, and a Karhunen Loeve transform (KLT) tracker is used for tracking characteristic points; and 2) the direction of each tracked characteristic point between adjacent frames is calculated, a sine value is used for representing the vector direction theta, a mean value of the theta is calculated to determine the center c, and a threshold value a is set to eliminate vector directions with larger change; the absolute value of theta-c represents the absolute distance; when the absolute value of theta-c is less than or equal to a, a tracked data result of the KLT tracker is not changed; and when the absolute value of theta-c is larger than a, the tracking points are eliminated, therefore, the optimized characteristic points are obtained. The invention provides the characteristic point optimization method for the three-dimensional reconstruction of the video scene, which effectively improves the accuracy.
Description
technical field [0001] The present invention relates to technical fields such as image processing, computer vision, calculation methods, mathematics, numerical methods, video processing, and three-dimensional reconstruction, especially the method for determining feature points during three-dimensional reconstruction of video. Background technique [0002] In recent years, the problem of recovering structure from motion has been a very important problem in the field of computer vision, and many researchers have devoted themselves to solving this problem. 3D reconstruction from video is a very important problem. In recent years, 3D reconstruction has been widely used, such as aerospace vehicles, robot navigation, reconstruction of 3D models of sculptures and historical monuments, 3D animation and Visual inspection, etc. The goal of this problem can be briefly described as follows. A video of a scene of interest is obtained from a single camera, and then we need to calculate t...
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IPC IPC(8): G06T17/00
Inventor 陈胜勇王月辉汪晓妍
Owner 日照新睿招商发展有限公司