School of Fine Arts, Hunan Normal University, Changsha 410006, China.
School of Physical Education, Hunan Normal University, Changsha 410006, China.
Comput Intell Neurosci. 2022 Apr 27;2022:2819269. doi: 10.1155/2022/2819269. eCollection 2022.
In order to improve the artistic expression effect of photographic images, this article combines the deep learning model to conduct multicamera photographic image art research in BERT motion. Moreover, this article analyzes the external parameter errors caused in the calibration process and uses the checkerboard in the common field of view to calibrate the spatial coordinates of the corners of the board in multiple camera coordinate systems. In addition, this article aims to match the spatial coordinates of the corresponding points to each other and solve the rotation and translation matrix in the transformation process. Finally, this article uses the LM algorithm to optimize the calibration parameters of the camera and combines the deep learning algorithm to perform image processing. The experimental research results show that the research method of multicamera photography image art in BERT motion based on the deep learning mode proposed in this article can effectively improve the expression effect of image art.
为了提高摄影图像的艺术表现效果，本文结合深度学习模型，对 BERT 运动中的多相机摄影图像艺术进行研究。此外，本文分析了标定过程中产生的外部参数误差，利用公共视场中的棋盘标定多个相机坐标系中板角的空间坐标。此外，本文旨在匹配对应点的空间坐标，并求解变换过程中的旋转和平移矩阵。最后，本文使用 LM 算法优化相机标定参数，并结合深度学习算法进行图像处理。实验研究结果表明，本文提出的基于深度学习模式的 BERT 运动中多相机摄影图像艺术的研究方法，可以有效地提高图像艺术的表现效果。
