红外与激光工程, 2015, 44 (4): 1115, 网络出版: 2016-01-26   

基于激光雷达距离像的目标3D姿态估计

3D pose estimation of target based on ladar range image
作者单位
1 哈尔滨工业大学 光电子技术研究所 可调谐激光技术国家级重点实验室,黑龙江 哈尔滨 150080
2 齐齐哈尔大学 应用技术学院,黑龙江 齐齐哈尔 161006
摘要
在激光雷达目标识别中,目标姿态的精确估计可以有效地简化识别过程。现有的PDVA算法主要是针对地面结构化目标而提出的一种3D目标姿态估计方法。该方法利用模型坐标系(MCS)各个坐标轴的正方向向量来确定目标的三维姿态角,其有效性通过实验得到了验证。但该方法在确定MCS各坐标轴的正方向向量时,所消耗的时间比较多,影响了算法的执行效率。文中提出了一种改进的PDVA算法,利用聚类中心邻域判别CCND法来加速MCS各坐标轴的正方向向量的确定过程。采用四种地面军用车模型目标进行了仿真实验,实验结果显示,改进的PDVA算法的平均运行时间约占PDVA算法的66%,极大地提高了目标3D姿态估计的执行效率。
Abstract
In the target recognition of ladar, the accurate estimation of target pose can effectively simplify the recognition process. The existing PDVA algorithm as a method of target 3D pose estimation is mainly for ground structured targets. This method uses the planar normals of rigid targets as the vectors in the positive direction of the axes in model coordinate system(MCS) to estimate the 3D pose angles of targets, and its effectiveness has been verified by experiments. However, it is time consuming when determining the positive direction vectors of the axes in MCS and affecting the efficiency of the algorithm. In this paper, an improved PDVA algorithm was proposed and a method of clustering center neighborhood discriminant(CCND) was used for accelerating the determination process of positive direction vectors of the axes in MCS. The simulation experiments were performed with four military vehicle models. The results show that the average running time of the improved PDVA algorithm only accounts for about 66% of the PDVA algorithm, and it greatly improves the efficiency of target 3D pose estimation.

吕丹, 孙剑峰, 李琦, 王骐. 基于激光雷达距离像的目标3D姿态估计[J]. 红外与激光工程, 2015, 44(4): 1115. Lv Dan, Sun Jianfeng, Li Qi, Wang Qi. 3D pose estimation of target based on ladar range image[J]. Infrared and Laser Engineering, 2015, 44(4): 1115.

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