基于深度图像分割与物体跟踪的增强现实系统  

Augmented Reality System Based on Depth Image Segmentation and Object Tracking

作　　者：杨家博 杨刚[1] 杨猛[1] 

机构地区：[1]北京林业大学信息学院,北京100083

出　　处：《系统仿真学报》2017年第11期2788-2795,共8页Journal of System Simulation

基　　金：中央高校基本科研业务费专项资金(2015ZCQ-XX)

摘　　要：提出一种能实现虚、实物体互动的增强现实解决方案。该方案中,采用Kinect等设备获取现实场景的深度图像,并基于深度图像对实景中的物体进行分割及动态跟踪。在场景分割时,提出一种基于先验知识的分割策略,首先识别出场景中先验存在的大平面,然后再对剩下的点云数据进行聚类,该方式对室内桌面场景分割效果良好。在物体跟踪时,采用了基于粒子滤波的三维跟踪算法,该过程中同样可以通过先验的大平面信息进行加速。该方法为实现虚、实物体互动提供了一种高效、便捷的实现方案。In this paper, an augmented reality scheme that can achieve the virtual-real objects＇ interaction effectively is proposed. The depth camera, such as Kinect, is adopted to capture the depth image of scene, and then the segmentation and dynamic tracking of the scene objects are implemented based on the depth image. In the scene segmentation, we propose a scene segmentation strategy based on the prior knowledge. The large plane objects existing in the scene are firstly recognized according to the prior knowledge. Then, the clustering segmentation is applied to the remaining points to get the scene objects. This strategy is very efficient for the indoor desktop-scene segmentation. In the object tracking, we adopt the three dimensional tracking algorithm based on particle filtering. The tracking process can also be accelerated by using the prior large plane information. This paper provides an efficient scheme for implementing the virtual-real objects＇ interaction.

关 键 词：增强现实 深度图像分割 物体跟踪 虚实交互 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]