陀螺仪在基于Hash结构的三维重建中的应用

Application of Gyroscope in 3D Reconstruction Based on Hash Structure

针对3D重建过程中出现深度相机突然运动,导致相机无法正确跟踪重建场景,提出了一种结合陀螺仪与基于Hash结构的Kinect Fusion 3D重建的方法.将陀螺仪得到的位姿与ICP算法得到的位姿通过扩展卡尔曼滤波器(EKF)数据融合,获得更加精确的位姿,改进了原始算法的3D重建效果.实验测试结果表明,该算法可以得到更加精确的系统位姿预测模型,在相机突然运动时仍然能够实现有效跟踪.

In order to track camera and reconstruct scene correctly when depth camera moves suddenly leadingto a failure of tracking reconstructed scene,a new 3D reconstruction method,which combines the gyroscope with the KinectFusion algorithm based on Hash structure,is proposed. A more precise pose can be obtained by a data fusion of the extended Kalman filter which integrates the pose data from gyroscope and that from the ICP algorithm,hence improving the effect of 3D reconstruction. Experimental tests show that this algorithm can obtain more accurate predictive model of the system pose and track camera effectively when depth camera moves suddenly.