Pedestrian movement mode classification method and device and electronic equipment
The invention provides a pedestrian movement mode classification method and device and electronic equipment. The method comprises the following steps: acquiring original trajectory data of each pedestrian in a plurality of pedestrians; performing feature extraction on each piece of original trajecto...
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| creator | XIANG HENGMAO GAO XIJIAN ZHANG HENGCAI LI HAO LIANG YUCAI SUN JIUHU |
| description | The invention provides a pedestrian movement mode classification method and device and electronic equipment. The method comprises the following steps: acquiring original trajectory data of each pedestrian in a plurality of pedestrians; performing feature extraction on each piece of original trajectory data to obtain geometric features; converting the original trajectory data into a shop sequence visited by pedestrians; according to the shop sequence, in combination with the text attribute of the shop, generating a shop track semantic feature corresponding to each pedestrian; carrying out feature fusion on the geometric feature corresponding to each pedestrian and the store track semantic feature to obtain a moving mode feature; and clustering all the moving mode features to obtain pedestrian moving mode classification. According to the method, the shop features and the pedestrian movement features are combined, so that the pedestrian movement mode classification is closer to the actual activity law of pedestr |
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The method comprises the following steps: acquiring original trajectory data of each pedestrian in a plurality of pedestrians; performing feature extraction on each piece of original trajectory data to obtain geometric features; converting the original trajectory data into a shop sequence visited by pedestrians; according to the shop sequence, in combination with the text attribute of the shop, generating a shop track semantic feature corresponding to each pedestrian; carrying out feature fusion on the geometric feature corresponding to each pedestrian and the store track semantic feature to obtain a moving mode feature; and clustering all the moving mode features to obtain pedestrian moving mode classification. 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The method comprises the following steps: acquiring original trajectory data of each pedestrian in a plurality of pedestrians; performing feature extraction on each piece of original trajectory data to obtain geometric features; converting the original trajectory data into a shop sequence visited by pedestrians; according to the shop sequence, in combination with the text attribute of the shop, generating a shop track semantic feature corresponding to each pedestrian; carrying out feature fusion on the geometric feature corresponding to each pedestrian and the store track semantic feature to obtain a moving mode feature; and clustering all the moving mode features to obtain pedestrian moving mode classification. According to the method, the shop features and the pedestrian movement features are combined, so that the pedestrian movement mode classification is closer to the actual activity law of pedestr</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
| title | Pedestrian movement mode classification method and device and electronic equipment |
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