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AndrewJohnsonThesis.pdf (1.17 MB)

ETD Abstract Container

Abstract Header

Fragment Association Matching Enhancement (FAME) on a Video Tracker

Johnson, Andrew
http://rave.ohiolink.edu/etdc/view?acc_num=wright1399465180

Abstract Details

2014, Master of Science in Computer Engineering (MSCE), Wright State University, Computer Engineering.
In the field of surveillance, algorithms are developed to extract meaningful information out of a video feed captured via a camera. One type of algorithm used in the field of surveillance is a tracking algorithm. A tracking algorithm allows a user to watch the movement of an object in the camera's field of view. The tracker used in this thesis research is a feature aided tracker (FAT). The FAT uses both features and kinematics to generate tracks. However, camera movement will affect the tracker's ability to accurately track an object which poses a problem to the tracker. Specifically, the camera will introduce the multi-fragmentation problem to the tracker. Multi-fragmentation occurs when an object is marked with two tracks instead of a single track. By marking the object with two tracks, the tracker's performance and accuracy will decrease. This thesis research proposes the idea of matching features of small foreground objects (fragments) to create larger foreground objects. A pair of fragments will have their features calculated into a score. If the fragment pair's score is below a specific threshold, they will be matched to create a larger fragment. Many of the concepts used to design this tracking algorithm (FAME) stem from the fields of computer vision, pattern recognition, and tracking.
Thomas Wischgoll, Ph.D. (Advisor)
Juan Vasquez, Ph.D. (Committee Member)
Arthur Goshtasby, Ph.D. (Committee Member)
63 p.
Computer Engineering
Tracking, Computer Vision, Pattern Recognition

Recommended Citations

Citations

  • Johnson, A. (2014). Fragment Association Matching Enhancement (FAME) on a Video Tracker [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1399465180

    APA Style (7th edition)

  • Johnson, Andrew. Fragment Association Matching Enhancement (FAME) on a Video Tracker. 2014. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1399465180.

    MLA Style (8th edition)

  • Johnson, Andrew. "Fragment Association Matching Enhancement (FAME) on a Video Tracker." Master's thesis, Wright State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1399465180

    Chicago Manual of Style (17th edition)

wright1399465180
470
© 2014, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.