National University of Defense Technology

Crrc Zhuzhou Electric Locomotive Research Institute Co., Ltd.

Jie Jiang

Yingmei Wei

Lai Kang

Yuxiang Xie

Yuliang Wen

Wenqing Mei

Liang Bai

Yang Liu

Liang Hu

Quanqiang Zhou

Puhua Zhong

Cheng Li

Zhengfang Zhang

Jiahao Sun

Yuan Luo

Yujie Fang

Xianghan Wang

Junyan Yang

Xing Xin

Yin Zou

Yixiang He

Yuehu Shao

Provided are a control method, apparatus and device for an automatic train operation system. The method includes: acquiring multiple preset traction distribution strategies; determining, for each traction distribution strategy, a performance index of the traction distribution strategy; determining an optimal traction distribution strategy based on performance indexes of the multiple traction distribution strategies; and controlling the automatic train operation system based on the optimal traction distribution strategy.

Energy-saving control method for automatic train operation, and related device and readable storage medium

The disclosure relates to a method and a system for hand pose recognition, a device and a storage medium are disclosed in embodiments of the disclosure. The method includes: capturing a RGB image of a hand from a RGB camera and capturing a depth image of the hand from an active depth camera, so as to obtain a hand pose data set according to the RGB image and the depth image; processing the hand pose data set to obtain a 3D joint position, and taking the 3D joint position as a data set for training a software model; extracting the RGB image by a feature extractor based on a depth neural network to obtain a feature map of a hand pose; and processing the feature map according to an attention mechanism to obtain a global feature map of the hand pose.

Method and system for hand pose recognition, device and storage medium

The present disclosure provides a visual localization method and apparatus based on a semantic error image. The method includes: performing feature extraction for a target image, and obtaining at least one matching pair by performing feature matching for each extracted feature point and each three-dimensional point of a constructed three-dimensional scene model; obtaining a two-dimensional semantic image of the target image by performing semantic segmentation for the target image; and determining semantic information of each matching pair according to semantic information of each pixel of the two-dimensional semantic image; constructing a hypothesized pose pool including at least one hypothesized pose according to at least one matching pair; for each hypothesized pose, constructing a reprojection error image and a semantic error image; determining a hypothesized pose with a minimum reprojection error and a minimum semantic error as a pose estimation according to the reprojection error image and the semantic error image of each hypothesized pose. Optimal pose screening is performed using the semantic error image constructed based on a semantic error, so as to achieve good localization effect even in a case of significant change of a scene.

Visual localization method and apparatus based on semantic error image

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Hunan, China

Jie Jiang