Time-of-Flight(ToF) cameras developed rapidly in recent years, but its low resolution limits its application. In this paper, we propose a new method to estimate the object’s 3D pose using a single ToF camera. We use the Iterative Closest Points(ICP) algorithm based on the Normal Aligned Radial Feature(NARF) to achieve the pose estimation of the target. The experimental results show that this method can accurately estimate the 3D pose of an object using a low-resolution ToF camera.
Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.
In this paper, we proposed a new method to improve the resolution of depth image. This method uses a high-resolution color image as a reference. We also use the bilateral filtered image as the guide image, and obtains the reconstructed image through joint bilateral filter and guidance filter. The experimental results show that this method can enhance the spatial resolution of the depth image and effectively eliminate the ringing effect and artifacts.