Sheng-Yu Wang

LIDAR-Camera Calibration For Semantic 3D Point Cloud Retrieval

Over this summer, I will be doing research on autonomous driving focusing on integrating and synchronizing data from laser radar sensor, which is also known as LIDAR, and multiple camera view. Autonomous driving has been a popular research subject recently, and it is really important to improve accuracy for the decision making by the algorithm. Since the output decision of the autonomous driving system is based on the information which sensors received from the environment, the accuracy of the decision making relies heavily on the integrity and the richness of the data. By integrating synchronized data from both LIDAR and multiple camera views, one can retrieve accurate semantic 3D information of the environment. In other words, the autonomous car can then perceive not only 3D positions, but also the object type, including people, roads, cars, etc., of the corresponding position. These data will be instrumental for the algorithm to perform decision making in a more accurate and reliable fashion.

Message to Sponsor

Dear Zara Fund, I would like to express my appreciation for your generosity in support of this summer research experience. In this summer, the SURF program made me more confident as a researcher and solidified my interests towards AI and computer vision research. Also, I improved many research skills, including presenting skills, reasoning skills, and etc. It was because of your generous support that I could have this wonderful opportunity. Again, thank you so much for all you've done for SURF!
  • Major: Computer Science
  • Sponsor: Zara Fund
  • Mentor: Trevor Darrell