caa a22 4500 60544756X CHVBK 20210128100132.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s11042-013-1806-0 doi (NATIONALLICENCE)springer-10.1007/s11042-013-1806-0 Background modeling and its evaluation for complex scenes [Elektronische Daten] [Li Sun, Wenjuan Sheng, Yiqing Liu] We present a new approach for modeling background in complex scenes that contain unpredicted motions caused e.g. by wind over water surface, in tree branches, or over the grass. The background model of each pixel is defined based on the observation of its spatial neighborhood in a recent history, and includes up to K ≥ 1 $K \ge 1$ modes, which defines the frequently appeared patterns at the given pixel position in the color space, ranked in decreasing order of occurrence frequency. Foreground regions can then be detected by comparing the intensity of an observed pixel to the high frequency modes of its background model. Experiments show that our spatial-temporal background model is superior to traditional related algorithms in cases for which a pixel encounters modes that are frequent in the spatial neighborhood without being frequent enough in the actual pixel position. As an additional contribution, our paper also proposes an original assessment method, which has the advantage of avoiding the use of costly handmade ground truth sequences of foreground objects silhouettes. Springer Science+Business Media New York, 2014 Background subtraction nationallicence Background modeling nationallicence Multiple modes nationallicence Sun Li School of Information Science and Technology, East China Normal University, 200241, Shanghai, China aut Sheng Wenjuan School of Automation Engineering, Shanghai University of Electric Power, 200090, Shanghai, China aut Liu Yiqing School of Information Science and Technology, East China Normal University, 200241, Shanghai, China aut Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/11(2015-06-01), 3947-3966 1380-7501 74:11<3947 2015 74 11042 https://doi.org/10.1007/s11042-013-1806-0 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11042-013-1806-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sun Li School of Information Science and Technology, East China Normal University, 200241, Shanghai, China aut NATIONALLICENCE 700 1- Sheng Wenjuan School of Automation Engineering, Shanghai University of Electric Power, 200090, Shanghai, China aut NATIONALLICENCE 700 1- Liu Yiqing School of Information Science and Technology, East China Normal University, 200241, Shanghai, China aut NATIONALLICENCE 773 0- Multimedia Tools and Applications Springer US; http://www.springer-ny.com 74/11(2015-06-01), 3947-3966 1380-7501 74:11<3947 2015 74 11042