Computer Vision Seminar – Shadow removal


Course Homepage:

Lecture 1 – Perception of shadows   (9/11/05)

The perception of cast shadows
Pascal Mamassian, David C. Knill and Daniel Kersten

Depth, Shape, Rigidity, from Cast Shadows

Geometry of Shadows
Knill, Mamassian and kersten (1997)
Journal of the Optical Society of America A 14:3216-3232

Also interesting:
Why cast shadows are expendable: Insensitivity of human
observers and the inherent ambiguity of cast shadows in pictorial art
Perception, 2004, volume 33, pages 1369-1383

Jayme Jacobson, Steffen Werner



Lecture 2 – Lecture 3  Creating shadows (computer graphics)    (16-23/11/05) 
2D local symmetry : Ribbons, SATs , Smooth Local Symmetries.
Projected Planar Shadows, Shadow Volumes, Stencil Shadow Volumes
Shadow Z-buffer, hard and Soft Shadows

Tutorial and citations within:


A Survey of Real-time Soft Shadows Algorithms

Hasenfratz J.-M.; Lapierre M.; Holzschuch N.; Sillion F.; IMAG-INRIA A.G.

Computer Graphics Forum, Volume 22, Number 4, December 2003, pp. 753-774(22)


J. Blinn. Me and my (fake) shadow. IEEE Computer Graphics Application, 8(1):82--86, 1988.

F. C. Crow. Shadow algorithms for computer graphics. In Computer Graphics (Proceedings of SIGGRAPH 77), volume 11, pages 242--248,  1977.

Lecture X – Shape from Shadow    (NOT GIVEN)
3D structure from shadow, depth from shadow

Belheumer; D. Kriegman, "What Shadows Reveal About Object Structure," accepted for publication in JOSA, in press.


Belheumer; D. Kriegman "What Do Shadows Reveal About Object Structure?"

Proc. Fifth European Conf. on Computer Vision, vol. 2, pp. 399—414, 1998.




Lecture 4 – Shadow Detection in video   (30/11/05)
Detecting Moving Shadows: Algorithms and Evaluation

Andrea Prati, Ivana Mikic, Mohan M. Trivedi, Rita Cucchiara,

IEEE Transactions On Pattern Analysis And Machine Intelligence, Vol. 25, No. 7, July 2003

Analysis and Detection of Shadows in Video Streams: A Comparative Evaluation

Prati, Cucchiarra, Mikic, Trivedi

And citations within (see me for list of possible references)

Good comparison table for shadow detection in:

Choose from:

Deterministic model-based approaches to detect that exploit gray level, local, and static features:


D. Koller, K. Daniilidis, and H.H. Nagel, “Model-Based Object

Tracking in Monocular Image Sequences of Road Traffic Scenes,”

Int’l J. Computer Vision, vol. 10, pp. 257-281, 1993.


M. Kilger, “A Shadow Handler in a Video-Based Real-Time Traffic

Monitoring System,” Proc. IEEE Workshop Applications of Computer Vision, pp. 11-18, 1992.



Statistical approaches:

Nonparametric approaches that use color, global, and dynamic features for enhancing object detection


C. Jiang and M.O. Ward, “Shadow Identification,” Proc. IEEE Int’l

Conf. Computer Vision and Pattern Recognition, pp. 606-612, 1992.



Assuming known scene and illuminant parameters (frame differences)

J. Stauder, R. Mech, and J. Ostermann, “Detection of Moving Cast

Shadows for Object Segmentation,” IEEE Trans. Multimedia, vol. 1,

no. 1, pp. 65-76, Mar. 1999.


Tracking by subtraction

Y. Sonoda and T. Ogata, Separation of moving objects and their shadows, and application to tracking of loci in the

monitoring images, Proceedings of the 4th International Conference on Signal Processing 1998, Vol. 2, 1261-1264,



A whole system approach - physical models

Physical Models for Moving Shadow and Object Detection in Video

Sohail Nadimi and Bir Bhanu

Ieee Transactions On Pattern Analysis And Machine Intelligence, Vol. 26, No. 8, August 2004




Lecture 5 – Using Color and Color Invariance     (7/12/05)

E. Salvador, P. Green, and T. Ebrahimi.

Shadow identification and classification using invariant color models.

In Proceedings of ICASSP 01, volume 3, pages 1545--1548. IEEE, 2001.


Cast shadow segmentation using invariant color features

Elena Salvador,a Andrea Cavallaro,b,* and Touradj Ebrahimi


Color Invariance

J.M. Geusebroek, R. van den Boomgaard, A.W.M. Smeulders, H. Geerts

IEEE PAMI December 2001 (Vol. 23, No. 12)   pp. 1338-1350


Shadow removal from a real picture

International Conference on Computer Graphics and Interactive Techniques archive

 Masashi Baba Naoki Asada   

Proceedings of the SIGGRAPH 2003 conference on Sketches & applications


Shadow Removal from a Real Image Based on Shadow Density

Masashi Baba    Masayuki Mukunoki    Naoki Asada


Improving Shadow Suppression in Moving Object Detection with HSV Color Information

Rita Cucchiara, Costantino Grana, Massimo Piccardi, Andrea Prati, Stefano Sirotti



Lecture 6 – Shadow removal from Sequence of Images     (14/12/05)

Y. Weiss. Deriving intrinsic images from image sequences. In ICCV01, pages II:

68{75. IEEE, 2001.

Y. Matsushita and K. Nishino, “Illumination normalization with time-dependent intrinsic images

for video surveillance,” IEEE Trans. Pattern Anal. Mach. Intell., 26, pp. 1336-1348 (2004).


Lecture 7 – Intrinsic Images using learning (Classifiers)      (21/12/05)

Recovering Intrinsic Images from a Single Image

 Tappen, M. F., Freeman, W. T., and Adelson, E. H. Advances in Neural Information Processing Systems no. 15 (NIPS 2002 Proceedings),

1367-1374 (2003).

M. Bell and W. T. Freeman. Learning local evidence for shading and reflection.

Proceedings International Conference on Computer Vision, 2001

Image shadow removal using pulse coupled neural network.

X.D. Gu, D. H. Yu, , L. M Zhang,

IEEE Trans. on Neural Networks,vol.16 , pp.692-698, 2005.

Lecture 8 – Shadow invariant image - I     (28/12/05)

Graham D. Finlayson, Steven D. Hordley, and Mark S. Drew, "Removing Shadows from Images", European Conference on Computer Vision,

ECCV'02 Vol.4, Lecture Notes in Computer Science Vol. 2353, pp. 823-836, 2002.

Graham D. Finlayson and Steven D. Hordley, "Color Constancy at a Pixel", Journal of the Optical Society of America A, 18, 253-264 (2001)

Finlayson - II   invariant image + reconstruction using retinex

Graham D. Finlayson, Steven D. Hordley, and Mark S. Drew, "Removing Shadows From Images using Retinex", Color Imaging Conference,

pp. 73-79, November 2002.


Edwin H. Land, "The Retinex Theory of Color Vision," Scientific American, Vol. 237, No. 6, pp. 108-128, December 1977

(Also other Retinex papers)

Lecture 9 – Shadow Tracking     (4/1/06)
(using Snakes)


"Shadow Resistant Tracking using Inertia Constraints", Hao Jiang and Mark S. Drew, Pattern Recognition 2005, To appear.


Hao Jiang and Mark S. Drew, "Tracking Objects with Shadows", Image and Video Communications and Processing 2003,

editors Bhaskaran  Vasudev, Touradj Ebrahimi, T. Russell Hsing, and Andrew G. Tescher, pp. 512-521.


M. Kass, A. Witkin, and D. Terzopoulos, ``Snakes - Active Contour Models'' International Journal of Computer Vision, 1(4): 321-331, 1987.
(Or other papers on snakes)

Lecture 10 – Applications     (11/1/06)

Automatic generation of consistent shadows for augmented reality

 Katrien Jacobs Jean-Daniel Nahmias Cameron Angus  Alex Reche Celine Loscos  Anthony Steed 

ACM International Conference Proceeding Series; Vol. 112 archive

Proceedings of the 2005 conference on Graphics interface

Dynamic Shadow Elimination for Multi-Projector Displays.

Rahul Sukthankar, Tat-Jen Cham, Gita Sukthankar.

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2001.


Dynamic Shadow Removal from Front Projection Displays.

Christopher Jaynes, Stephen Webb, Matt Steele, Michael Brown, W. Brent Seales.

Proceedings of the IEEE Visualization 2001.