A Target Recognition Method Based on Feature Geometric Gains
A target recognition and geometry technology, applied in image analysis, image enhancement, instruments, etc., can solve problems such as poor target recognition effect, unsatisfactory feature matching and false matching rejection, etc., to improve accuracy and effectiveness. , the effect of improving time efficiency
Active Publication Date: 2021-09-21
ZHONGBEI UNIV
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[0004] In view of the unsatisfactory results of key point detection, feature matching and mismatch elimination in the existing 3D point cloud target recognition process, and the poor effect of target recognition in complex scenes containing noise, different resolutions, and overlapping occlusions, etc., The present invention proposes a method for target recognition based on feature geometric returns
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[0058] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.
[0059] Such as figure 1 As shown, the target recognition method based on feature geometric income in this embodiment includes steps 1 to 7:
[0060] Step 1, use the SIFTKeypoint algorithm provided in the PCL library to detect the key points of the point cloud model and scene, and obtain the key point sets and sums of the model and scene respectively, which are recorded as with where N M and N S are the number of candidate keypoints for the model and scene, respectively.
[0061] Among them, the key to calculate the point cloud model and scene is to use the SIFTKeypoint algorithm provided in the PCL library as an existing technology, and will not be described in detail here.
[0062] Step 2, for the model and scene key point set P obtained in step 1 M and P S point p in i Perform edge point detection. Think if point p i The minimum ...
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The present invention specifically relates to a target recognition method based on feature geometric benefits, which solves the problem of unsatisfactory results of key point detection, feature matching and false match elimination in the existing 3D point cloud target recognition process, and the problem of noise and resolution differences And there are problems such as poor recognition of targets in complex scenes such as occlusion and overlap. Firstly, the step of removing edge keypoints is added in the keypoint detection stage; secondly, the nearest neighbor is used to remove ambiguous feature matching pairs in the feature matching stage; then, in the hypothesis generation stage, this paper proposes a feature geometric return method, Aggregate the correct matches and generate a hypothesis transformation; finally, in the hypothesis verification stage, perform fine registration to verify the hypothesis transformation and accurately estimate the pose of the target. This method is suitable for the recognition of target models in messy 3D point cloud scenes, and is used for target recognition in machine vision. It can be widely used in areas such as unmanned vehicle driving, robotics, automated assembly, and intelligent monitoring.
Description
technical field [0001] The invention belongs to the technical field of machine vision, and in particular relates to a target recognition method based on feature geometric returns. This method is suitable for the recognition of target models in messy 3D point cloud scenes, and is used for target recognition in machine vision. Background technique [0002] Vision is an important means for human beings to perceive and understand the world. Computer vision technology allows computers to acquire, process, analyze and identify images by simulating human vision to realize the understanding of the real world. Object recognition has always been one of the research hotspots in the field of computer vision, and can be widely used in areas such as unmanned vehicle driving, robotics, automated assembly, and intelligent monitoring. The purpose of target recognition is to identify the target of interest from the scene and obtain its attitude information such as position and orientation. ...
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IPC IPC(8): G06T7/12G06T7/136G06T7/33
CPCG06T2207/10028G06T7/12G06T7/136G06T7/344
Inventor 熊风光贾勇杰韩燮况立群
Owner ZHONGBEI UNIV