Track motion mode recognition method and device

A pattern recognition and trajectory motion technology, applied in character and pattern recognition, biological neural network models, instruments, etc., can solve problems such as low accuracy and complex process, and achieve the effect of improving accuracy and good recognition.
CN110866477APending Publication Date: 2020-03-06PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
PLA STRATEGIC SUPPORT FORCE INFORMATION ENG UNIV PLA SSF IEU
Publication Date
2020-03-06

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Abstract

The invention relates to a track motion mode recognition method and device, and belongs to the technical field of artificial intelligence. The track motion mode recognition method includes the steps:through a deep learning mode, automatically extracting depth features of preprocessed to-be-identified track data, wherein the obtained depth features have a better identification degree, so that theaccuracy of mode identification can be significantly improved; and meanwhile, when carrying out pretreatment, converting the track data into the grid data containing the multi-dimensional information,wherein the positions of the grids represent the positions of the users, and the grid sequence reflects the geographic space characteristics and the geometrical characteristics of the user track, andthe pixels of the grid represent the average speed of the user in the grid and reflect the kinematicity characteristics of the user track, so as to guarantee that the converted track data can fully express the representative characteristics of the mobile user track, and the accuracy of pattern recognition is further improved.
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Description

technical field

[0001] The invention relates to a trajectory motion pattern recognition method and device, belonging to the technical field of artificial intelligence. Background technique

[0002] Analyzing the movement patterns of mobile user trajectories is a key means to understand the spatio-temporal characteristics of user behavior, traffic conditions, and the user's environment. User travel usually includes specific motion patterns, such as individual users choose different destinations and routes, different means of transportation (taxi, bus, walking, bicycle, etc.), ship users perform different navigation activities (fishing, oil transportation, etc.) , transportation of goods, towing, sightseeing, etc.). Information about specific motion patterns is usually not actively reported by users, and such information has a wide range of application values โ€‹โ€‹for practical applications, such as intelligent transportation systems, urban traffic management, early warning syst...

Claims

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