A Parallel Framework for Scene Understanding
Wenwen Zhang, Jiangong Wang, Kunfeng Wang · 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI) · 2021
Different related computer vision tasks make it possible to understand and analyze the scene totally. However, there is no useful framework combining different tasks for scene understanding. In this paper, we investigate the current state of scene understanding from different aspects relying on different computer vision tasks and propose an effective framework based on the theory of parallel vision to combine different tasks for scene understanding. With the maintained artificial scene throughout time from the proposed framework, we can understand the scene in an elegant way. To explain our proposed framework, a case study is given.