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A feature enhancement method of LiDAR point cloud cell body based on graph convolution
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A feature enhancement and laser radar technology, applied in image enhancement, image analysis, image data processing, etc., to improve target detection accuracy, alleviate negative effects, and improve accuracy
Active Publication Date: 2022-02-22
TSINGHUA UNIV
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Therefore, the target segmentation problem caused by cell body division is an inherent defect of the cell body method.
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Embodiment 2
[0094] Embodiment 2 of the present invention may further provide a computer device, including: at least one processor, a memory, at least one network interface, and a user interface. The individual components in the device are coupled together via a bus system. It can be understood that the bus system is used to realize the connection communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus and a status signal bus.
[0095] Wherein, the user interface may include a display, a keyboard, or a pointing device (for example, a mouse, a trackball (trackball), a touch panel, or a touch screen, and the like.
[0096] It can be understood that the memory in the disclosed embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory. Wherein, the non-volatile memory may be a read-only memory (Read-Only Memory, ROM), a programmable read-on...
Embodiment 1
[0101]The method in Embodiment 1 may be applied to or implemented by a processor. A processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The above-mentioned processor may be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field Programmable Gate Array, FPGA) or other programmable Logic devices, discrete gate or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in Embodiment 1 can be realized or executed. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like. The steps of the method discl...
Embodiment 3
[0105] Embodiment 3 of the present invention provides a non-volatile storage medium for storing computer programs. Each step of the method in Embodiment 1 can be realized when the computer program is executed by the processor.
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Abstract
The present invention discloses a method for enhancing cell body characteristics of laser radar data based on graph convolution. The method includes: step 1) performing cell body division and information extraction on radar point cloud data collected in real time to obtain cell body data; step 2 ) Composing the somatic data to form a graph structure; step 3) inputting the graph structure into the graph convolution unit, performing feature enhancement on each node in the graph structure, and inputting the feature-enhanced graph structure into the graph convolution unit again, Repeat multiple times until the number of cycles is reached; Step 4) Transfer the enhanced cell body features output by the last graph convolution unit to the back-end target detection network to complete the target detection task. The method of the present invention proposes to fuse information between cell bodies, which improves the ability of each cell body to capture instance target information, and improves the accuracy of the 3D target detection method.
Description
technical field [0001] The present invention relates to the field of automatic driving, in particular to a graph convolution-based laser radar point cloud cell feature enhancement method. Background technique [0002] In unmanned driving technology, environmental perception is the most basic functional module. Unmanned vehicles rely on lidar, millimeter-wave radar, camera sensors, etc. to perceive the environment, such as lane line detection, 3D target detection, etc., which are the basic functions of the environmental perception module. Environmental perception is the feedback of environmental information for unmanned vehicles, which is used to make decisions and control the driving behavior of vehicles, so as to ensure the driving safety of vehicles and road safety. [0003] 3D object detection is a very important part of the environment perception task, which needs to detect all meaningful objects around the driverless car, including traffic participants such as vehicles...
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