Detecting shadows is needed for object detection methods because shadows often have a harmful effect on the result. Shadow detection methods based on shadow models are proposed. The shadow model should be updated to detect shadows which are not included in the learning data. When it is updated, outlier should be removed from them. In this paper, a data selection method for removing outlier from the data is proposed. The proposed method selects data by information of object regions and Normalized Distance. Using only the selected data results in obtaining better shadow regions because the better shadow model can be constructed. Results are demonstrated by the experiments using the real videos.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org