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Hardware implementation method for ORB feature point extraction with good real-time performance

A feature point extraction and hardware implementation technology, applied in the field of computer vision, can solve the problems of huge computing resources, unsuitable intelligent robots, high system power consumption, etc. Effect

Pending Publication Date: 2020-08-25
XI AN JIAOTONG UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Compared with FPGA, although the processing speed of GPU is faster, GPU requires huge computing resources and high system power consumption when used, and is not suitable for embedded or small intelligent robots.

Method used

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  • Hardware implementation method for ORB feature point extraction with good real-time performance
  • Hardware implementation method for ORB feature point extraction with good real-time performance
  • Hardware implementation method for ORB feature point extraction with good real-time performance

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Embodiment Construction

[0043] Below in conjunction with accompanying drawing, implementation process of the present invention is described in further detail:

[0044] The present invention designs a four-stage assembly line structure to realize screening of feature points. According to the symmetry of the position of the sampling point on the discretized Bresenham diagram of the central pixel point, the pixel point is divided into four parts according to the vertical direction and the horizontal direction, and each time a pixel point is selected in each group of data, and the position of the pixel point into a symmetrical relationship. After the sampling points are divided into four groups, the gray value comparison with the central pixel point is carried out respectively. Each stage of the four-stage pipeline compares a set of data, and two judgment mechanisms are designed for each stage of the pipeline to screen feature points.

[0045] The present invention carries out pipeline architecture des...

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Abstract

The invention discloses a hardware implementation method for ORB feature point extraction with good real-time performance. The hardware implementation method for ORB feature point extraction with goodreal-time performance mainly solves the problems that in an existing visual SLAM system, feature point extraction consumes long time, and image matching efficiency is low. According to the implementation scheme, the method comprises the steps that 1, constructing an image feature point screening four-level assembly line; 2, constructing a feature point main direction angle calculation 11-level pipeline architecture; 3, obtaining the gradient direction of the feature points by using the gray centroid of the image block, and performing Gaussian sampling according to the sampling coordinates ofthe main direction rotation descriptor; and 4, designing a two-stage synchronous linear shift buffer structure and an inter-module data stream transmission structure; the method has the advantages ofhigh image processing speed, high accuracy, high platform portability and the like, and can be used in a real-time visual SLAM system to expand the application scene of the SLAM system.

Description

technical field [0001] The invention belongs to image matching in the field of computer vision, and relates to the hardware implementation of basic modules such as the extraction of FAST feature points, the calculation of BRIEF descriptors, and image matching, the design of data processing pipeline structures, and the design of data stream buffer structures. The hardware implementation method of ORB feature point extraction. Background technique [0002] SLAM (simultaneous localization and mapping) technology, that is, real-time positioning and map reconstruction. Its original meaning is that the robot equipped with sensors can build an environmental map through the movement of the robot in an unknown environment without obtaining any environmental information, and at the same time realize the real-time positioning of its own position and posture, and finally realize the real-time autonomy of the robot. Localization and map reconstruction of the environment. In various ind...

Claims

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Application Information

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IPC IPC(8): G06T1/20G06T1/60G06T7/66G06K9/46
CPCG06T1/20G06T1/60G06T7/66G06V10/40Y02D10/00
Inventor 张瑞智李倩梅魁志张增同城辉屈鹏飞张向楠常蕃
Owner XI AN JIAOTONG UNIV
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