Wertheim School of Optometry and Vision Science, UC Berkeley, Minor Hall, Berkeley, CA, USA.
Redwood Center for Theoretical Neuroscience, UC Berkeley, Evans Hall, Berkeley, CA, USA.
Behav Res Methods. 2024 Jan;56(1):32-42. doi: 10.3758/s13428-022-01888-3. Epub 2022 Jul 25.
We describe the design and performance of a high-fidelity wearable head-, body-, and eye-tracking system that offers significant improvement over previous such devices. This device's sensors include a binocular eye tracker, an RGB-D scene camera, a high-frame-rate scene camera, and two visual odometry sensors, for a total of ten cameras, which we synchronize and record from with a data rate of over 700 MB/s. The sensors are operated by a mini-PC optimized for fast data collection, and powered by a small battery pack. The device records a subject's eye, head, and body positions, simultaneously with RGB and depth data from the subject's visual environment, measured with high spatial and temporal resolution. The headset weighs only 1.4 kg, and the backpack with batteries 3.9 kg. The device can be comfortably worn by the subject, allowing a high degree of mobility. Together, this system overcomes many limitations of previous such systems, allowing high-fidelity characterization of the dynamics of natural vision.
我们描述了一种高保真可穿戴式头部、身体和眼部跟踪系统的设计和性能,该系统相对于以前的此类设备有了显著的改进。该设备的传感器包括双目眼动追踪器、RGB-D 场景相机、高帧率场景相机和两个视觉里程计传感器,总共有十台相机,我们以超过 700MB/s 的数据速率对其进行同步和记录。传感器由一个针对快速数据采集进行了优化的迷你 PC 操作,并由一个小电池组供电。该设备记录了受试者的眼睛、头部和身体位置,同时记录了受试者视觉环境的 RGB 和深度数据,具有较高的空间和时间分辨率。头戴式设备仅重 1.4 公斤,带电池的背包重 3.9 公斤。该设备可由受试者舒适佩戴,允许高度的移动性。总的来说,该系统克服了以前此类系统的许多限制,允许对自然视觉的动态进行高保真度的描述。