引入视觉显著性的多特征融合跟踪

引入视觉显著性的多特征融合跟踪*

佟威1，和箫1+，卢英1,2

1.西安建筑科技大学信息与控制工程学院，西安710055

2.西安建筑科技大学建筑学院，西安710055

Visual Saliency and Multi-Feature Fusion for Object Tracking *

TONG Wei 1,HE Xiao 1+,LU Ying 1,2

1.School of Information and Control Engineering,Xi 'an University of Architecture and Technology,Xi 'an 710055,China

2.School of Architecture,Xi 'an University of Architecture and Technology,Xi 'an 710055,China

+Corresponding author:E-mail:251347576@https://www.360docs.net/doc/8510594219.html,

TONG Wei,HE Xiao,LU Ying.Visual saliency and multi-feature fusion for object tracking.Journal of Fron-tiers of Computer Science and Technology,2017,11(3)：438-449.

Abstract:Traditionally,most tracking algorithms use the single feature to describe the object.In view of the insuffi-ciency of traditional tracking algorithms in complicated background,this paper puts forward an object tracking algo-rithm used by multi-feature fusion and visual saliency.Firstly,this paper adopts a visual saliency mechanism for manipulating color histogram data to get saliency feature,uses a hybridstrategy that fuses the BRISK (binary robust invariant scalable keypoints)feature and saliency information to describe the image,and then extracts the object-foreground model and object-background model.Moreover,the dynamic feature is extracted by the bidirectional op-tical flow and error metric and is fused with the static feature which is extracted by the adaptive searching mecha-nism.Finally,based on the data of matching and tracking procedure in the previous frame,this paper evaluates the object ’s scale,rotation and center,and obtains the new target location in the current frame.Experiments show that the proposed algorithm can handle the tracking in the complicated background,and adapt to strong illumination changes,partial occasions,fast motion and so on.The high accuracy and robustness of the proposed algorithm are *The National Natural Science Foundation of China under Grant No.51209167(国家自然科学基金);the Natural Science Foundation of Shaanxi Province under Grant No.2013JM8022(陕西省自然科学基金);the Youth Foundation of Xi ’an University of Architec-ture and Technology under Grant No.QN1423(西安建筑科技大学青年基金).

Received 2016-01,Accepted 2016-03.

CNKI 网络优先出版:2016-03-08,https://www.360docs.net/doc/8510594219.html,/kcms/detail/11.5602.TP.20160308.1005.002.html

ISSN 1673-9418CODEN JKYTA8

Journal of Frontiers of Computer Science and Technology

1673-9418/2017/11(03)-0438-12

doi:10.3778/j.issn.1673-9418.1601070E-mail:fcst@https://www.360docs.net/doc/8510594219.html, https://www.360docs.net/doc/8510594219.html, Tel:+86-10-89056056万方数据