AI Vision

In Neuvition LiDAR innovative application solutions, AI vision is frequently used as an auxiliary. The system collects real-time data of the measured object through visual sensors, the host performs real-time processing, analysis, and storage of the source video images. In visual analysis, it identifies the measured objects within a specified range and marks them in the video stream. The video stream is then transmitted through internal interfaces for data fusion processing to provide visual features for 3D data collected by LiDAR. This technology is mainly used for foreign object intrusion detection.
The process of foreign object intrusion detection is as follows:
Collect information of field environments from image data streams which are obtained by industrial-grade camera via LAN.
Use deep neural network algorithms to detect specified objects within a specified range in real time, including feature extraction, position detection, and object classification.
Use deep neural network algorithms to intelligently recognize objects in real time and perform pixel-level classification, mainly including trains, cars, pedestrians, and objects larger than 25*25cm.
Use Kalman filter algorithm to track and compensate for the real-time position of the object.
The results of the measured object are transmitted to data fusion for processing which adds visual features to 3D LiDAR data.

In addition to the above steps, Neuvition LiDAR and its AI vision algorithm services also support various functions such as image recognition, video stream recognition, point cloud recognition and text recognition, to flexibly meet user needs.

In terms of application scenarios, this technology can be widely used in fields such as rail transit，city roads, and industrial production, providing more efficient, intelligent and safer solutions for the public.

Image Recognition
Video Stream Recognition
Point Cloud Recognition
Text Recognition
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