Abstract: A method for analyzing a number of people includes an image shooting step and a front-end analyzing step. In the image shooting step, a first image and a second image are obtained. In the front-end analyzing step, a foreground object analysis is operated, and a plurality of foreground objects located at a region of interest in the first image are obtained. A human body detection is operated, and at least one human body and a location thereof of the second image are obtained. An intersection analysis is operated, and the location of the human body is matched to the first image. A number of people estimation is operated to estimate the number of the people according to the first covering ratio, a number of the human body, and a second covering ratio of all the foreground objects to the region of interest.

Abstract: A method for analyzing a number of people includes an image shooting step and a front-end analyzing step. In the image shooting step, a first image and a second image are obtained. In the front-end analyzing step, a foreground object analysis is operated, and a plurality of foreground objects located at a region of interest in the first image are obtained. A human body detection is operated, and at least one human body and a location thereof of the second image are obtained. An intersection analysis is operated, and the location of the human body is matched to the first image. A number of people estimation is operated to estimate the number of the people according to the first covering ratio, a number of the human body, and a second covering ratio of all the foreground objects to the region of interest.

Abstract: A method and a system for generating dynamic map information with environment information are provided, wherein the system includes a cloud server, multiple relay hosts distributed around the environment and multiple vehicle devices each installed respectively in different vehicles. Each vehicle device includes a LiDAR sensor and a camera for sensing the environment to respectively generate point cloud data and image data. When the point cloud data from different vehicles are transmitted to a neighboring relay host, the relay host performs a multi-vehicle data integration mode to merge the point cloud data and obtain 3D coordinates information of objects in the environment according to the merged data. Based on the 3D coordinates information of objects, the cloud server generates and transmits dynamic map information to the vehicles. By sharing sensing data of different vehicles, the sensing area of each vehicle is expanded to mitigate dark zones or blind zones.

Abstract: A method and a system for generating dynamic map information with environment information are provided, wherein the system includes a cloud server, multiple relay hosts distributed around the environment and multiple vehicle devices each installed respectively in different vehicles. Each vehicle device includes a LiDAR sensor and a camera for sensing the environment to respectively generate point cloud data and image data. When the point cloud data from different vehicles are transmitted to a neighboring relay host, the relay host performs a multi-vehicle data integration mode to merge the point cloud data and obtain 3D coordinates information of objects in the environment according to the merged data. Based on the 3D coordinates information of objects, the cloud server generates and transmits dynamic map information to the vehicles. By sharing sensing data of different vehicles, the sensing area of each vehicle is expanded to mitigate dark zones or blind zones.