Segmentation of soft shadows based on a daylight- and penumbra model

Authors:
Michael Nielsen;Claus B. Madsen
Affiliations:
Aalborg University, Computer Vision and Media Technology Laboratory, Aalborg, Denmark;Aalborg University, Computer Vision and Media Technology Laboratory, Aalborg, Denmark
Venue:
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Year:
2007

Citing 6
Cited 4

Removing Shadows from Images

ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
What Energy Functions Can Be Minimizedvia Graph Cuts?

IEEE Transactions on Pattern Analysis and Machine Intelligence
Cast shadow segmentation using invariant color features

Computer Vision and Image Understanding
An Iterative Optimization Approach for Unified Image Segmentation and Matting

ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Shadow identification and classification using invariant color models

ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Using real shadows to create virtual ones

SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis

Shadow Detection and Removal from Solo Natural Image Based on Retinex Theory

ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part I
Shadow Detection in Dynamic Scenes Using Dense Stereo Information and an Outdoor Illumination Model

Dyn3D '09 Proceedings of the DAGM 2009 Workshop on Dynamic 3D Imaging
Tricolor attenuation model for shadow detection

IEEE Transactions on Image Processing
Graph cut based segmentation of soft shadows for seamless removal and augmentation

SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper introduces a new concept within shadow segmentation for usage in shadow removal and augmentation through construction of an alpha overlay shadow model. Previously, an image was considered to consist of shadow and non-shadow regions. We construct a model that accounts for sunlit, umbra and penumbra regions. The model is based on theories about color constancy, daylight, and the geometry that causes penumbra. The behavior of the model is analyzed and a graph cut energy minimization is applied to estimate the alpha parameter. The approach is demonstrated on natural complex image situations. The results are convincing, but the alpha gradient in penumbra must be improved.