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Coupling eye-motion and ego-motion features for first-person activity recognition

机译:结合眼动和自我运动功能进行第一人称活动识别

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摘要

We focus on the use of first-person eye movement and ego-motion as a means of understanding and recognizing indoor activities from an “inside-out” camera system. We show that when eye movement captured by an inside looking camera is used in tandem with ego-motion features extracted from an outside looking camera, the classification accuracy of first-person actions can be improved. We also present a dataset of over two hours of realistic indoor desktop actions, including both eye tracking information and a high quality outside camera video. We run experiments and show that our joint feature is effective and robust over multiple users.
机译:我们专注于使用第一人称眼动和自我运动来理解和识别“内外”摄像系统中的室内活动。我们显示,当将内部看摄像机捕获的眼睛运动与从外部看摄像机提取的自我运动特征一起使用时,第一人称动作的分类准确性可以提高。我们还提供了一个超过两个小时的实际室内桌面操作的数据集,包括眼睛跟踪信息和高质量的室外摄像机视频。我们进行了实验,结果表明我们的联合功能在多个用户中均有效且强大。

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