Information Science and Technology College, Dalian Maritime University, Dalian 116026, China.
School of Microelectronics, Dalian University of Technology, Dalian 116024, China.
Sensors (Basel). 2019 Mar 14;19(6):1287. doi: 10.3390/s19061287.
The driver gaze zone is an indicator of a driver's attention and plays an important role in the driver's activity monitoring. Due to the bad initialization of point-cloud transformation, gaze zone systems using RGB-D cameras and ICP (Iterative Closet Points) algorithm do not work well under long-time head motion. In this work, a solution for a continuous driver gaze zone estimation system in real-world driving situations is proposed, combining multi-zone ICP-based head pose tracking and appearance-based gaze estimation. To initiate and update the coarse transformation of ICP, a particle filter with auxiliary sampling is employed for head state tracking, which accelerates the iterative convergence of ICP. Multiple templates for different gaze zone are applied to balance the templates revision of ICP under large head movement. For the RGB information, an appearance-based gaze estimation method with two-stage neighbor selection is utilized, which treats the gaze prediction as the combination of neighbor query (in head pose and eye image feature space) and linear regression (between eye image feature space and gaze angle space). The experimental results show that the proposed method outperforms the baseline methods on gaze estimation, and can provide a stable head pose tracking for driver behavior analysis in real-world driving scenarios.
驾驶员注视区域是驾驶员注意力的一个指标，在驾驶员活动监测中起着重要作用。由于点云变换的初始化不良，使用 RGB-D 相机和 ICP（迭代最近点）算法的注视区域系统在长时间头部运动下无法正常工作。在这项工作中，提出了一种在实际驾驶情况下连续驾驶员注视区域估计系统的解决方案，结合基于多区域 ICP 的头部姿势跟踪和基于外观的注视估计。为了初始化和更新 ICP 的粗略变换，采用具有辅助采样的粒子滤波器进行头部状态跟踪，这加速了 ICP 的迭代收敛。为了在大头部运动下平衡 ICP 的模板修正，应用了多个用于不同注视区域的模板。对于 RGB 信息，利用具有两级邻居选择的基于外观的注视估计方法，将注视预测视为邻居查询（在头部姿势和眼睛图像特征空间中）和线性回归（在眼睛图像特征空间和注视角度空间之间）的组合。实验结果表明，所提出的方法在注视估计方面优于基线方法，并且可以为实际驾驶场景中的驾驶员行为分析提供稳定的头部姿势跟踪。
