Abstract:
Hard shadows detection and removal from foreground masks is a challenging step in change detection. This paper gives a simple and effective method to address hard shadows...Show MoreMetadata
Abstract:
Hard shadows detection and removal from foreground masks is a challenging step in change detection. This paper gives a simple and effective method to address hard shadows. There are inside portion and boundary portion in hard shadows. Pixel-wise neighborhood ratio is calculated to remove the most of inside shadow points. For the boundaries of shadow regions, we take advantage of color constancy to eliminate the edges of hard shadows and obtain relative accurate objects contours. Then, morphology processing is explored to enhance the integrity of objects. The main contribution of this paper is to design an approximate estimation strategy for illumination invariant based on Lambertian reflectance model without prior knowledge. The proposed method is unsupervised and experimental results on six challenging sequences show the effectiveness and robustness of our approach.
Published in: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Date of Conference: 15-20 April 2018
Date Added to IEEE Xplore: 13 September 2018
ISBN Information:
Electronic ISSN: 2379-190X