Tracker/Camera Calibration for Accurate Automatic Gaze Annotation of Images and Videos.
Tracker/Camera Calibration for Accurate Automatic Gaze Annotation of Images and Videos.
复制标题
跟踪器/相机校准，可对图像和视频进行准确的自动注视注释。
DOI：
10.1145/3517031.3529643
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Manduchi,Roberto
中科院分区：
文献类型：
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作者：
Jindal,Swati;Kaur,Harsimran;Manduchi,Roberto
现代基于外观的视线跟踪算法需要大量的训练数据，其中观看者的图像用“地面实况”视线方向注释。获得凝视注释的标准方法是要求受试者注视特定的已知位置，然后使用头部模型来确定“凝视原点”的位置。我们建议使用IR凝视跟踪器在自然环境中生成凝视注释，不需要固定的目标点。这需要IR凝视跟踪器与相机的先前几何校准，使得由IR跟踪器产生的数据可以在相机的参考系中表示。这一贡献介绍了一个简单的跟踪器/摄像机校准过程的基础上的Pestival算法，并演示了其使用，以获得一个完整的表征凝视方向，可用于地面实况注释。
Modern appearance-based gaze tracking algorithms require vast amounts of training data, with images of a viewer annotated with “ground truth” gaze direction. The standard approach to obtain gaze annotations is to ask subjects to fixate at specific known locations, then use a head model to determine the location of “origin of gaze”. We propose using an IR gaze tracker to generate gaze annotations in natural settings that do not require the fixation of target points. This requires prior geometric calibration of the IR gaze tracker with the camera, such that the data produced by the IR tracker can be expressed in the camera’s reference frame. This contribution introduces a simple tracker/camera calibration procedure based on the PnP algorithm and demonstrates its use to obtain a full characterization of gaze direction that can be used for ground truth annotation.