Dual Exposure Stereo for Extended Dynamic Range 3D Imaging

Achieving robust stereo 3D imaging under diverse illumination conditions is challenging due to the limited dynamic range of conventional cameras, causing existing stereo depth estimation methods to suffer from under- or over-exposed images. In this paper, we propose dual-exposure stereo that combines auto-exposure control and dual-exposure bracketing to achieve stereo 3D imaging with extended dynamic range. Specifically, we capture stereo image pairs with alternating dual exposures, which automatically adapt to scene illumination and effectively distribute the scene dynamic range across the dual-exposure frames. We then estimate stereo depth from these dual-exposure stereo images by compensating for motion between consecutive frames. To validate our approach, we develop a robotic vision system, acquire real-world HDR stereo video datasets, and generate additional synthetic datasets. Experimental results demonstrate that our method outperforms existing exposure control methods.