The MPD data is collected by the built multi-modal awareness vehicle system. The data is recorded in real time by the industrial computer equipped with GPU. Six cameras and four LiDARs are set on top of the vehicle, and here is the sensors setup diagrams:
The vehicle speed is maintained at 40km / H during data collection. OpenMPD consists of consecutive frame fragments with each fragment lasting 5 seconds. For continuous image frames within 5 seconds, the camera annotates every other frame to obtain 100 labeled images. In addition, the mechanical LiDAR annotates each point cloud in succession within 5 seconds. To help researchers get a quick understanding on OpenMPD, we also provide the tutorials about how to use OpenMPD.
The OpenMPD dataset is designed for a complex situation in the real world. In this condition, we need the views of the data collection platform to be 360°. Therefore, we add one more camera facing the back of the vehicle.
Below is the parameters for all cameras:
Data propagation speed
Front_Left & Right
Side_Left & Right
In order to provide a 360° degree of the whole environment with LiDAR，we have placed a 128 beams LiDAR at the front rooftop of the vehicle which is also the main scene’s data collection device. Compared with those LiDARs with fewer beams, it can collect information from a far distance with data being more accurate and points denser. In order to overcome the problems of blind spots, we decide to place 2 LiDAR with 16 beams on both of the side and 1 LiDAR with 40 beams on the back to cover the all scope. We set all LiDARs to 10Hz.
Below is the parameters for all LiDARs:
Side_Left & Side_Right
Thanks Datatang（ https://www.datatang.ai , stock code: 831428), a leading artificial intelligence data service provider in the world, for providing tailored data services. Several of its annotation platforms have managed to cut down data processing costs by integrating automatic annotation tools. With high-quality training data services in place, Datatang has helped thousands of AI enterprises around the world improve the performance of AI models.