caa a22 4500 605540411 CHVBK 20210128100911.0 cr unu---uuuuu 210128e20151201xx s 000 0 eng 10.1007/s00371-014-1044-0 doi (NATIONALLICENCE)springer-10.1007/s00371-014-1044-0 Moving object tracking based on multi-independent features distribution fields with comprehensive spatial feature similarity [Elektronische Daten] [Zhiyong Li, Xiaoping Yu, Pengfei Li, Mervat Hashem] Obtaining the exact spatial information of moving objects is a crucial and difficult task during visual object tracking. In this study, a comprehensive spatial feature similarity (CSFS) strategy is proposed to compute the confidence level of target features. This strategy is used to determine the current position of the target among candidates during the tracking process. Given that the spatial information and appearance feature of an object should be considered simultaneously, the CSFS strategy offers the benefit of reliable tracking position decisions. Moreover, we propose an appearance-based multi-independent features distribution fields (MIFDFs) object representation model, which represents targets using spatial distribution fields with multiple features independently. This representation model can preserve a large amount of original spatial and feature data synthetically. Various experimental results show that the proposed method exhibits significant improvement in terms of tracking drift in complex scenes. In particular, the proposed approach outperforms other techniques in tracking robustness and accuracy in some challenging situations. Springer-Verlag Berlin Heidelberg, 2014 Object tracking nationallicence Distribution fields nationallicence Multi-independent features nationallicence Spatial feature similarity nationallicence Li Zhiyong College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut Yu Xiaoping College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut Li Pengfei College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut Hashem Mervat College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut The Visual Computer Springer Berlin Heidelberg 31/12(2015-12-01), 1633-1651 0178-2789 31:12<1633 2015 31 371 https://doi.org/10.1007/s00371-014-1044-0 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/s00371-014-1044-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Li Zhiyong College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut NATIONALLICENCE 700 1- Yu Xiaoping College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut NATIONALLICENCE 700 1- Li Pengfei College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut NATIONALLICENCE 700 1- Hashem Mervat College of Computer Science and Electronic Engineering, Hunan University, 410082, Changsha, China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/12(2015-12-01), 1633-1651 0178-2789 31:12<1633 2015 31 371