JCP 2014 Vol.9(9): 2167-2172 ISSN: 1796-203X
doi: 10.4304/jcp.9.9.2167-2172
doi: 10.4304/jcp.9.9.2167-2172
A Novel Fragments-based Similarity Measurement Algorithm for Visual Tracking
Jun Shang1, Chuanbo Chen2, Hu Liang1, He Tang2, and Mudar Sarem2
1School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China
College of Computer, Hubei University of Education, Wuhan, China
2School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China
Abstract—Various adaptive appearance models have been proposed to deal with the challenges in tracking objects such as occlusions, illumination changes, background clutter, and pose variation. In this paper, first, we present a novel Fragments-based Similarity Measurement algorithm for object tracking in video sequence. Both the target and the reference are divided by multiple fragments of the same size. Then, we find the similarity of each fragment with the overlapped smaller patches by comparing the average intensity value of the patches. The accuracy of the tracking results can be improved by adjusting the size of the patches. Finally we incorporate the global similarity measurement using two kinds of distances between them. This method encodes the color and the spatial information so that it can track non-rigid objects under complex scene. We use this coarse-to-fine method to get a balance between the accuracy and the computational cost. Extensive experiments are conducted to verify the efficiency and the reliability of our proposed algorithm in the realistic videos.
Index Terms—Visual tracking, appearance model, similarity measure
College of Computer, Hubei University of Education, Wuhan, China
2School of Software Engineering, Huazhong University of Science and Technology, Wuhan, China
Abstract—Various adaptive appearance models have been proposed to deal with the challenges in tracking objects such as occlusions, illumination changes, background clutter, and pose variation. In this paper, first, we present a novel Fragments-based Similarity Measurement algorithm for object tracking in video sequence. Both the target and the reference are divided by multiple fragments of the same size. Then, we find the similarity of each fragment with the overlapped smaller patches by comparing the average intensity value of the patches. The accuracy of the tracking results can be improved by adjusting the size of the patches. Finally we incorporate the global similarity measurement using two kinds of distances between them. This method encodes the color and the spatial information so that it can track non-rigid objects under complex scene. We use this coarse-to-fine method to get a balance between the accuracy and the computational cost. Extensive experiments are conducted to verify the efficiency and the reliability of our proposed algorithm in the realistic videos.
Index Terms—Visual tracking, appearance model, similarity measure
Cite: Jun Shang, Chuanbo Chen, Hu Liang, He Tang and Mudar Sarem, "A Novel Fragments-based Similarity Measurement Algorithm for Visual Tracking," Journal of Computers vol. 9, no. 9, pp. 2167-2172, 2014.
General Information
ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
-
Nov 14, 2019 News!
Vol 14, No 11 has been published with online version [Click]
-
Mar 20, 2020 News!
Vol 15, No 2 has been published with online version [Click]
-
Dec 16, 2019 News!
Vol 14, No 12 has been published with online version [Click]
-
Sep 16, 2019 News!
Vol 14, No 9 has been published with online version [Click]
-
Aug 16, 2019 News!
Vol 14, No 8 has been published with online version [Click]
- Read more>>