Robust HDR 3D reconstruction with an event camera via inverted spatial-shifting Gray-code encoding

Event cameras, with their significantly higher dynamic range and sensitivity to intensity variations compared to frame cameras, provide new possibilities for 3D reconstruction in high-dynamic-range (HDR) scenes.However, the binary event data stream produced by event cameras presents significant challenges for achieving high-precision and efficient 3D reconstruction.In addressing these issues, we observe that the binary projection inherent to Gray-code-based 3D reconstruction naturally aligns with the event camera's imaging mechanism.However, achieving high-accuracy 3D reconstruction using a Gray code remains hindered by two key factors: inaccurate boundary extraction and the degradation of high-order dense Gray code patterns due to spatial blurring.For the first challenge, we propose an inverted Gray code strategy to improve region segmentation and recognition, achieving more precise and easily identifiable Gray code boundaries.For the second challenge, we introduce a spatial-shifting Gray-code encoding method.By spatially shifting Gray code patterns with lower encoding density, a combined encoding is achieved, enhancing the depth resolution and measurement accuracy.Experimental validation across general and HDR scenes demonstrates the effectiveness of the proposed methods.