title: Preprocessing Depth maps from RGBD images captured by Kinnect device
body: <p>I'm working on a 3D Reconstruction project based on RGBD images captured by my Kinnect device. The input is an instance segmentation image and a depth map, and the output is a point cloud. <br />
  The problem is that my device is not very good. For a segmented object in the image (which has the same color for each pixel in that object), the depth value of that pixel is usually approximately the same. But for some pixel, will have much higher, or much lower, depth values. I call it irregular, or abnormal values. For example, an object in the image will have a depth value between 2800 and 3000. But there are some abnormal values, maybe higher than 3000: 3020, 3060, 3100; or maybe lower than 2800: 2520, 2400, or very low like 200, 300. <br />
  So the question is how can I detect these anomalies, and choose another suitable depth value to set? I have tried some clustering methods but I think they didn't work well, and it costs much time.<br />
  Thanks for watching my question.</p>