Semantic map lightweight method
The invention provides a semantic map lightweight method. The method comprises the following steps: extracting a significant trajectory of a region of interest; calculating local feature descriptors along the trajectory, extracting visual features, and performing vector coding on the local feature d...
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Main Authors | , , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
07.11.2023
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Subjects | |
Online Access | Get full text |
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Summary: | The invention provides a semantic map lightweight method. The method comprises the following steps: extracting a significant trajectory of a region of interest; calculating local feature descriptors along the trajectory, extracting visual features, and performing vector coding on the local feature descriptors; and finally, the encoded features are arranged in a tensor form, and discrimination features are obtained through tucker-3 tensor decomposition, so that the semantic map model is lightened. The method solves the problems that a semantic map is large in data size and large in storage difficulty, the transmission bandwidth, computing power and vehicle-mounted storage of an automobile are limited, and the semantic map and a reasoning model are difficult to operate.
本发明提供了一种语义地图轻量化方法,该方法包括感兴趣区域显著轨迹的提取;沿轨迹计算局部特征描述符,提取视觉特征,并将局部特征描述符进行矢量编码;最后,将编码后的特征以张量形式进行排列,通过tucker-3张量分解得到判别特征,以此实现语义地图模型轻量化。本发明的方法解决了语义地图数据量较大,存在存储难度大,汽车的传输带宽、算力和车载存储受到限制,语义地图和推理模型存在难以运行的问题。 |
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Bibliography: | Application Number: CN202310646371 |