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An Unstructured Array Camera System with Scalable Capability

Unstructured array camera systems break through the optical limitations of a single camera and blaze a new trail to high-performance imaging by combining cameras. However, existing solutions use an array of cameras with fixed focal lengths and the same hardware model, lacking flexibility and practicality. The previous works rely on known focal length values, and the image processing methods are too complex to generate ultra-high-resolution videos in real-time. Inspired by image matching and deep learning methods, we proposed an unstructured array camera system with scalable capability that can freely change the focal length of each camera. The proposed cross-scale image matching method based on feature matching can quickly and accurately search the positions of local-view cameras. The image warping algorithm based on deep neural networks can efficiently composite ultra-high-resolution videos in real-time. Furthermore, the color alignment based on the LAB format is used for addressing the problem of different brightness and color between cameras. Experimental results show that our proposed system can use any camera or phone to composite ultra-high-resolution videos in real-time with flexibility, robustness, and efficiency.