Insights into Batch Selection for Event-camera Motion Estimation - Datasets

See https://github.com/event-driven-robotics/batch-selection-experiments for examples on how to read and process the data.

Simulated datasets were used to accurately have a ground-truth of 3 DoF camera rotation, for valid training and evaluation. Four photo-realistic simulated environments from UnrealCV Zoo were selected as they are publicly available indoor scenes and include diverse lighting textures, shadows, reflections and object clutter. The camera was positioned inside the virtual room and rotated along all its three axes randomly at a variety of speeds. Frames were generated at >1 kHz from which the event-stream is generated using log-image-difference  techniques. Five velocity trajectories were used for arch1, four velocity trajectories were used for arch2, and three trajectories for arch3. Including the final room dataset, a total of 13 different datasets (each with a different velocity trajectory) cover a total of 190 seconds of data. Note: room is split into 3 archived files.

Please cite:

Valerdi, J.L., Bartolozzi, C. and Glover, A., 2023. Insights into Batch Selection for Event-Camera Motion Estimation. Sensors, 23(7), p.3699.

@article{valerdi2023insights,
title={Insights into Batch Selection for Event-Camera Motion Estimation},
author={Valerdi, Juan L and Bartolozzi, Chiara and Glover, Arren},
journal={Sensors},
volume={23},
number={7},
pages={3699},
year={2023},
publisher={MDPI}
}

如需了解如何读取与处理该数据集的示例，请访问：https://github.com/event-driven-robotics/batch-selection-experiments

本数据集采用仿真数据，以精准获取相机3自由度（3 DoF）旋转的真实标注（ground-truth），用于规范的模型训练与评估。我们选取了UnrealCV Zoo提供的4个照片级真实感仿真环境，这些环境均为公开可用的室内场景，包含丰富的光照纹理、阴影、反射效果与物体杂乱分布。将相机置于虚拟房间内，使其沿三个轴以不同速率随机旋转。以超过1 kHz的帧率生成图像帧，随后通过对数图像差分（log-image-difference）技术生成事件流（event-stream）。arch1采用5条速度轨迹，arch2采用4条，arch3则采用3条。连同最终的room数据集在内，本项目共包含13组独立数据集（每组均对应一条独特的速度轨迹），总数据时长为190秒。注意：room数据集被拆分为3个归档文件。

请引用以下文献：
Valerdi, J.L.、Bartolozzi, C.与Glover, A.，2023年。《事件相机运动估计的批量选择方法探析》（Insights into Batch Selection for Event-Camera Motion Estimation）。《传感器》（Sensors），第23卷第7期，第3699页。

@article{valerdi2023insights,
title={Insights into Batch Selection for Event-Camera Motion Estimation},
author={Valerdi, Juan L and Bartolozzi, Chiara and Glover, Arren},
journal={Sensors},
volume={23},
number={7},
pages={3699},
year={2023},
publisher={MDPI}
}