Stereo Matching Based on Random Speckle Projection for Dynamic 3D Sensing

Real-time 3D sensing has many important applications in areas such as robotic navigation, virtual reality and human-computer interaction. A variety of techniques have been developed for the determination of 3D geometry information such as binocular vision, structured light and their combination. However, existing non-contact optical 3D sensing approaches have their own limitations in the process of 3D information calculation. The reliability of binocular vision is limited to textures of the object surface, and the measuring accuracy of the method based on structured-light projection is limited to the stability of the light generator and the number of projected images. In this paper, we will combine random speckle projection with stereo matching algorithms to study the related problems on 3D measurement in the scene. An unique random speckle pattern is projected to encode the object surface to reduce the influence of projector flickering, and improve the accuracy of stereo matching. Besides, we take advantage of temporal consistency to reduce the range of disparity updating to improve the speed of 3D sensing further. The tests performed on real captured images confirm the validity of our approach.