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DPCS2018+64+分层式三维室内地图分类方法及更新机制研究

冯光升,张晓雪,王慧强,李冰洋   

  1. 哈尔滨工程大学
  • 收稿日期:2018-08-08 修回日期:2018-08-28 发布日期:2018-08-28
  • 通讯作者: 张晓雪

Hierarchical 3D Indoor Map Classification Method and Updating Mechanism

  • Received:2018-08-08 Revised:2018-08-28 Online:2018-08-28

摘要: 摘 要: 现有的地图更新方法,在室内地图环境下的效果并不理想,针对这种情况,本文提出了一种分层式的室内地图更新方法。其以室内物体的活动性为参数,进行层次的划分,来减少更新数据的数量,并利用卷积神将网络对室内数据进行归属层次的判定。实验结果表明,相比于没有进行分层的增量式更新方法与版本式更新方法,本文提出的方法无论是在更新时间还是更新数据量上都有很大的提升。

关键词: 关键词: 室内地图 地图更新方法 分层式更新 卷积神经网络

Abstract: Abstract: The existing map updating method is not ideal under the indoor map environment. In view of this situation, this paper proposes a layered indoor map updating method. It uses the activity of indoor objects as a parameter to divide the levels to reduce the amount of updated data, and uses Convolution to determine the network's level of ownership of the indoor data. The experimental results show that compared with the incremental update method and the version update method without layering, the method proposed in this paper has greatly improved both in the update time and the update data amount.

Key words: Keywords: indoor map map update method tiered update convolutional neural network