- 专利标题: Method for Classifying a Tracked Object
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申请号: US17643586申请日: 2021-12-09
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公开(公告)号: US20220188582A1公开(公告)日: 2022-06-16
- 发明人: Weimeng Zhu , Florian Kaestner , Zhiheng Niu , Arne Grumpe
- 申请人: Aptiv Technologies Limited
- 申请人地址: BB St. Michael
- 专利权人: Aptiv Technologies Limited
- 当前专利权人: Aptiv Technologies Limited
- 当前专利权人地址: BB St. Michael
- 优先权: EP20212928.4 20201210
- 主分类号: G06K9/62
- IPC分类号: G06K9/62 ; G06N3/04 ; G01S13/88
摘要:
A method is provided for classifying a tracked object in an environment of a vehicle. The vehicle includes a plurality of radar sensors and a processing device configured to establish a neural network. According to the method, local radar detections are captured from an object in the environment of the vehicle via the radar sensors. Based on the local radar detections, point features and tracker features are determined. The point features are encoded via point encoding layers of the neural network, whereas the tracker features are encoded via track encoding layers of the neural network. A temporal fusion of the encoded point features and the encoded tracker features is performed via temporal fusion layers of the neural network. The tracked object is classified based on the fused encoded point and tracker features via classifying layers of the neural network.