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Underground parking lot high-precision visual positioning method and system based on VGG + NetVLAD

An underground parking lot and visual positioning technology, applied in the field of computer vision, can solve the problems of poor generalization ability and poor robustness, and achieve the effect of fast search speed, strong robustness and high accuracy

Pending Publication Date: 2021-11-12
JIANGSU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional hand-designed feature extraction methods require professional knowledge and a complex parameter tuning process. At the same time, each method is specific to a specific application, so the generalization ability and robustness are poor

Method used

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  • Underground parking lot high-precision visual positioning method and system based on VGG + NetVLAD
  • Underground parking lot high-precision visual positioning method and system based on VGG + NetVLAD
  • Underground parking lot high-precision visual positioning method and system based on VGG + NetVLAD

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0074] Example 1. Visual Map of Safety Exit Signs in Underground Parking Lot

[0075] Such as figure 1 Shown, the present invention utilizes the safe exit sign in underground parking lot to make visual map, and the concrete operation that realizes this method is as follows:

[0076] 1. Data collection stage: collect the image of the safety exit sign in the target underground parking lot, and record the required data information.

[0077] Use the selected camera to shoot the signs in the parking lot, pay attention to: the collected signs cover the parking lot as much as possible; the image content includes certain scene features; the sign is complete in the image; each sign collects several images, including different lighting conditions, different Shooting distance, different shooting angles.

[0078] The data information corresponding to each sign recorded during shooting includes: the location information of the sign; the color, shape and geometric size of the sign. In t...

Embodiment 2

[0089] Embodiment 2. High-precision visual positioning method for underground parking lot

[0090] Combine below Figure 4 The algorithm flow of the positioning method further describes the present invention. In the target underground parking lot, take an image of the safety exit sign at the location, and use the prepared sign map to realize high-precision positioning of the underground parking lot, including the following steps:

[0091] 1. Types of identification marks.

[0092] Input the captured image of the underground parking lot as the query image into the YOLOv3 sign detection network model, detect the sign in the scene, identify the sign type, return the sign type and the image coordinates of the detection frame, and call the set of signs of this type in the map at this time;

[0093] 2. Search for the nearest logo image.

[0094] Input the query image into the feature extractor to extract the visual vector, and the visual vector V of the query image q Visual vect...

Embodiment 3

[0118] Embodiment 3. Positioning result of an underground parking lot

[0119] Collect sign image data in the target underground parking lot, use the method proposed by the present invention to make a visual map of the safety exit sign, and test the positioning method proposed by the present invention. The changing factors of the test image include different light intensity, different shooting distances and angles.

[0120] The present invention realizes visual positioning based on the method of deep learning (YOLOv3 and VGG+NetVLAD), and can recognize the specific identity of the input test image under different illumination, distance and angle, and the recognition accuracy rate exceeds 90%.

[0121] Then extract the feature points of the sign, and realize the pose calculation through the homography matrix, and the distance from the camera to the sign plane can be obtained. Some test error results are as follows: Figure 5 As shown, the minimum distance error is about 3mm, an...

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Abstract

The invention discloses an underground parking lot high-precision visual positioning method and system based on VGG + NetVLAD. The method specifically comprises the following steps: 1, a data acquisition stage: acquiring emergency exit sign data information in a target parking lot; 2, a network model establishment and training stage: establishing and training a mark detection model and a global feature extraction model; 3, a map making stage: making a map by using the trained network model; and 4, a positioning realization stage: resolving the pose between the camera and the mark by using plane homography to realize real-time positioning. The visual map is made by using the original emergency exit sign in the parking lot, the scheme is simple, other deployment is not needed, the method is realized only through a monocular camera, the cost is reduced, the positioning precision can reach the sub-meter level, and the invention can be applied to mobile equipment and also can be applied to intelligent driving automobiles.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a VGG+NetVLAD-based high-precision visual positioning method and system for an underground parking lot. Background technique [0002] Due to the characteristics of dark light, more occlusion, and high repetition of scenes in underground parking lots, "difficult to park" and "difficult to find a car" have always been problems in underground parking lots, which not only cost car owners a lot of time to find, but also affect vehicles. flow efficiency. [0003] At present, GPS is the most widely used positioning technology, but its positioning accuracy is poor, and in some special locations such as tunnels, under bridges, underground parking lots, etc., it cannot receive signals, so it is mostly used for outdoor positioning. Visual positioning is to obtain location information by taking images of the current location through the camera. It has very important applications in smart cars...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/22G06F18/241G06F18/214
Inventor 李祎承冯锋蔡英凤王海蒋卓一朱镇杨东晓
Owner JIANGSU UNIV