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Calibration: Accurately calibrate your cameras (intrinsic and stereo extrinsics).

Minimize noise: Stereo disparity algorithms are affected by noise in the images, so make sure that your illumination gives good contrast without over or underexposing details. Make sure your sensor's sensitivy (ISO) is low to reduce speckle. Try to avoid lossy compression on images from your sensors (JPG, RLE, and other compression techniques) - these produce noise that humans do not notice, but algorithms do.

Adjust parameters: There are many filtering parameters by which you can tweak the SGBM or BM stereo disparity algorithms to provide calmer output. See e.g. Answer #182049

Temporal or Spatial Filtering: you can try smoothing individual frames with e.g. median filter with a small radius, or for a static scene, over time, accumulating multiple depth images and averaging them.

Pattern projection: If there is not enough detail of high contrast in a large area, then using a projector to illuminate a random dot pattern on both objects can assist filling in holes. This also needs gain adjusted so as not to be of adequate contrast.

Generally, some set of these techniques can help.

Calibration: Accurately calibrate your cameras (intrinsic and stereo extrinsics).

Minimize noise: Stereo disparity algorithms are affected by noise in the images, so make sure that your illumination gives good contrast without over or underexposing details. Make sure your sensor's sensitivy (ISO) is low to reduce speckle. Try to avoid lossy compression on images from your sensors (JPG, RLE, and other compression techniques) - these produce noise that humans do not notice, but algorithms do.

Adjust parameters: There are many filtering parameters by which you can tweak the SGBM or BM stereo disparity algorithms to provide calmer output. See e.g. Answer #182049

Temporal or Spatial Filtering: you can try smoothing individual frames with e.g. median filter with a small radius, or for a static scene, over time, accumulating multiple depth images and averaging them.

Pattern projection: If there is not enough detail of high contrast in a large area, then using a projector to illuminate a random dot pattern on both objects can assist filling in holes. This also needs gain adjusted so as not to be of to provide adequate contrast.

Generally, some set of these techniques can help.

Calibration: Accurately calibrate your cameras (intrinsic and stereo extrinsics).

Minimize noise: Stereo disparity algorithms are affected by noise in the images, so make sure that your illumination gives good contrast without over or underexposing details. Make sure your sensor's sensitivy (ISO) is low to reduce speckle. Try to avoid lossy compression on images from your sensors (JPG, RLE, and other compression techniques) - these produce noise that humans do not notice, but algorithms do.

Adjust parameters: There are many filtering parameters by which you can tweak the SGBM or BM stereo disparity algorithms to provide calmer output. See e.g. Answer #182049

Temporal or Spatial Filtering: you can try smoothing individual frames with e.g. median filter with a small radius, or for a static scene, over time, accumulating multiple depth images and averaging them.

Pattern projection: If there is not enough detail of high contrast in a large area, then using a projector to illuminate a random dot pattern on both objects can assist filling in holes. This also needs gain adjusted so as to provide adequate contrast.

Generally, some set of these techniques can help.