用神经网络生成能融入环境的隐形标记，实现6自由度精准定位。
Ninja Codes: Neurally Generated Fiducial Markers for Stealthy 6-DoF Tracking
- 通过编码器将任意图像转为视觉上几乎无感的隐形标记
- 在室内光照下稳定提供6自由度定位，可打印于普通纸张
- 适合对美观性要求高的机器人与增强现实场景
本文提出Ninja Codes，一种由神经网络生成的隐形标志物，可自然融入各类真实环境。通过编码器网络对任意图像施加视觉上微小的修改，生成可在常规打印纸上用标准彩色打印机打印的标记；将这些标记贴于表面后，任何配备现代RGB摄像头并具备推理能力的设备均可实现隐蔽的6-DoF位置跟踪。实验表明，在常见室内光照条件下，Ninja Codes能可靠提供定位信息，同时成功隐藏于多样的环境纹理中。该技术特别适用于传统标识物外观显眼、不适宜用于美学或隐蔽性要求较高的场景，如机器人导航和增强现实应用。
原文摘要 · Abstract (English)
In this paper we describe Ninja Codes, neurally generated fiducial markers that can be made to naturally blend into various real-world environments. An encoder network converts arbitrary images into Ninja Codes by applying visually modest alterations; the resulting codes, printed and pasted onto surfaces, can provide stealthy 6-DoF location tracking for a wide range of applications including robotics and augmented reality. Ninja Codes can be printed using standard color printers on regular printing paper, and can be detected using any device equipped with a modern RGB camera and capable of running inference. Through experiments, we demonstrate Ninja Codes' ability to provide reliable location tracking under common indoor lighting conditions, while successfully concealing themselves within diverse environmental textures. We expect Ninja Codes to offer particular value in scenarios where the conspicuous appearance of conventional fiducial markers makes them undesirable for aesthetic and other reasons.
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