Vehicle-mounted surround vision algorithm based on heterogeneous architecture

In order to take advantage of the powerful advantages of heterogeneous devices and improve the robustness of the vehicle-mounted surround vision algorithm(VSVA), several key technologies of VSVA are improved in the paper. Firstly, computationally intensive tasks are calculated by heterogeneous Graphics Processing Unit(GPU), at the same time, so as to adapt to the VSVA, the memory model and computing model of GPU are optimized. Then a perspective transformation algorithm based on geometric constraints is proposed to improve the quality of the transformed image. Finally, an image alignment and fusion algorithm based on a calibration board is proposed, which reduces the complexity of the algorithm while ensuring the robustness of the image fusion algorithm. The paper compares the proposed algorithm with the traditional algorithm, the test results show that the proposed algorithm has good robustness and the overall performance of the VSVA is improved to 95.39%, the proposed algorithm can be widely used.