Consider the Head Movements! Saccade Computation in Mobile Eye-Tracking

Negar Alinaghi, Ioannis Giannopoulos
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引用次数: 1

Abstract

Saccadic eye movements are known to serve as a suitable proxy for tasks prediction. In mobile eye-tracking, saccadic events are strongly influenced by head movements. Common attempts to compensate for head-movement effects either neglect saccadic events altogether or fuse gaze and head-movement signals measured by IMUs in order to simulate the gaze signal at head-level. Using image processing techniques, we propose a solution for computing saccades based on frames of the scene-camera video. In this method, fixations are first detected based on gaze positions specified in the coordinate system of each frame, and then respective frames are merged. Lastly, pairs of consecutive fixations –forming a saccade- are projected into the coordinate system of the stitched image using the homography matrices computed by the stitching algorithm. The results show a significant difference in length between projected and original saccades, and approximately 37% of error introduced by employing saccades without head-movement consideration.
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考虑头部的动作!移动眼动追踪中的扫视计算
跳跃性眼球运动被认为是任务预测的合适代理。在移动眼动追踪中,跳眼事件受到头部运动的强烈影响。补偿头部运动效应的常见尝试要么完全忽略跳眼事件,要么融合由imu测量的凝视和头部运动信号,以模拟头部水平的凝视信号。利用图像处理技术,提出了一种基于场景摄像机视频帧的视跳计算方案。该方法首先根据每帧坐标系中指定的注视位置检测注视点,然后对各帧进行合并。最后,利用拼接算法计算出的单应性矩阵,将连续注视对(形成一个扫视)投影到拼接图像的坐标系中。结果表明,投影的扫视和原始的扫视在长度上有显著的差异,在不考虑头部运动的情况下使用扫视会产生大约37%的误差。
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