In 3D computer graphics and computer vision, a depth map is an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint. The term is related (and may be analogous) to depth buffer, Z-buffer, Z-buffering, and Z-depth.[1] The "Z" in these latter terms relates to a convention that the central axis of view of a camera is in the direction of the camera's Z axis, and not to the absolute Z axis of a scene.


Two different depth maps can be seen here, together with the original model from which they are derived. The first depth map shows luminance in proportion to the distance from the camera. Nearer surfaces are darker; further surfaces are lighter. The second depth map shows luminance in relation to the distances from a nominal focal plane. Surfaces closer to the focal plane are darker; surfaces further from the focal plane are lighter, (both closer to and also further away from the viewpoint).[citation needed]


Fog effect
Shallow depth of field effect

Depth maps have a number of uses, including:

Generating and reconstructing 3D shapes from single or multi-view depth maps or silhouettes[3]



  1. ^ Computer Arts / 3D World Glossary[permanent dead link], Document retrieved 26 January 2011.
  2. ^ Eisemann, Elmar; Schwarz, Michael; Assarsson, Ulf; Wimmer, Michael (19 April 2016). Real-Time Shadows. CRC Press. ISBN 978-1-4398-6769-3.
  3. ^ a b "Soltani, A. A., Huang, H., Wu, J., Kulkarni, T. D., & Tenenbaum, J. B. Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes With Deep Generative Networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 1511-1519)". GitHub.
  4. ^ Schuon, Sebastian, et al. "Lidarboost: Depth superresolution for tof 3d shape scanning[dead link]." Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. IEEE, 2009.
  5. ^ Malik, Aamir Saeed, ed. Depth map and 3D imaging applications: algorithms and technologies: algorithms and technologies[dead link]. IGI Global, 2011.
  6. ^ Mousavi, Seyed Muhammad Hossein; Mirinezhad, S. Younes (January 2021). "Iranian kinect face database (IKFDB): a color-depth based face database collected by kinect v.2 sensor". SN Applied Sciences. 3 (1). doi:10.1007/s42452-020-03999-y. ISSN 2523-3963.

See also