⚡ 本页包含 AI 生成的分析内容，仅供参考
该论文提出了一款用于视觉受损者导航设备的低功耗3D视觉处理器，工作在0.6V低电压下，功耗仅8mW。它通过处理立体或ToF相机生成的深度图像，将其转换为3D点云，以提取环境空间信息，从而辅助导航。
devices, such as stereo and time-of-flight (ToF) cameras, measure distances to the observed points and generate a depth image where each pixel represents a distance to the corresponding location. The depth image can be converted into a 3D point cloud using simple linear operations. This spatial information provides detailed understanding of the environment and is currently employed in a wide range of applications such as human motion capture [1]. However, its distinct characteristics from conventional color images necessitate different approaches to efficiently extract useful information. This paper describes a low-power vision processor for processing such 3D image data. The processor achieves high energy-efficiency through a parallelized reconfigurable architecture
Dongsuk Jeon1,*, Nathan Ickes1, Priyanka Raina1,
Hsueh-Cheng Wang1, Daniela Rus1, Anantha Chandrakasan1 Massachusetts Institute of Technology, Cambridge, MA, now at Seoul National University, Suwon, Korea 1 * 3D imaging