Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Analysis and detection of shadows in video streams: a comparative evaluation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)
Prati, A. ; Dip. di Ingegneria dell''Informazione, Modena Univ., Italy ; Cucchiara, R. ; Mikic, I. ; Trivedi, M.M.

Robustness to changes in illumination conditions as well as viewing perspectives is an important requirement for many computer vision applications. One of the key factors in enhancing the robustness of dynamic scene analysis is that of accurate and reliable means for shadow detection. Shadow detection is critical for correct object detection in image sequences. Many algorithms have been proposed in the literature that deal with shadows. However, a comparative evaluation of the existing approaches is still lacking. In this paper, the full range of problems underlying the shadow detection is identified and discussed. We classify the proposed solutions to this problem using a taxonomy of four main classes, deterministic model and non-model based, and statistical parametric and nonparametric. Novel quantitative (detection and discrimination accuracy) and qualitative metrics (scene and object independence, flexibility to shadow situations and robustness to noise) are proposed to evaluate these classes of algorithms on a benchmark suite of indoor and outdoor video sequences.

Published in:

Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on  (Volume:2 )

Date of Conference:

2001